DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT CONTENTS

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2 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT CONTENTS DEPARTMENT DIRECTOR S STATEMENT...3 PERSONNEL...5 EDUCATION...8 COURSES GIVEN IN COURSES GIVEN IN THESES Bachelor s Degrees Diploma Theses Doctoral Theses RESEARCH Tampere International Center For Signal Processing, TICSP TICSP Workshops Awards and Nominations RESEARCH GROUPS Networked multimedia systems group Transforms and Spectral Methods Audio, Image and Video Analysis (IVA) Audio Research Group NAMU Lab A Pseudo-Volumetric, Immaterial 3D Display M 2 obsi group Digital Filters and Filter Banks Team Information Theoretic Methods for Signal Compression and Genomic Signal Processing Knowledge Mining Team Sleep and Sensory Signal Analysis Group Computational systems biology research group PUBLICATIONS Referee articles Other journal articles Artilcles published in referred conferece proceedings Articles in conference proceedings Articles in collections Books Editor and rewiewer duties Keynote papers Presentations Examiners / opponents of dissertations Other statemet of assessment of professorship New Memberships... 78

3 3 DEPARTMENT DIRECTOR S STATEMENT DEPARTMENT DIRECTOR S STATE- MENT The biennium 2008 and 2009 has been an era of changes in the organization of the Tampere University of Technology (TUT). The faculty division was reorganized. From the 1 st of January 2008 there have been only five faculties. The Institute of Signal Processing changed it s name to the Department of Signal Processing. The Department of Signal Processing belongs to the faculty of Computing and Electrical Engineering. The strategies of the new faculties were defined and the strategies of the departments were checked. The faculty Boards and the boards for the major programs were nominated. Many new administrative software tools were introduced, for instance ESS, PROJO, Tietovarasto, and Total. The full cost model for projects was introduced and a new type of budgeting was started. The preparations for the reintroduction of the four period system in education in fall 2010 were begun. Finally, during the year 2009 the university started the process to become a private foundation university. The role of signal processing has changed. This can be seen by observing new products and services. What was earlier viewed as digital signal processing now forms only a small part of the new concept of signal processing. The concept might be more adequately described as the methods of analyzing, manipulating and presenting natural information. The new communication and imaging technologies have vastly increased the capabilities of individuals to interact with the surrounding world in a multimodal way. The recent advances in biology, such as microarrays, have opened ways to a true understanding of biological processes. The future of signal processing is in developing techniques that enable natural interaction using modalities that are most natural for humans, and in developing modeling tools for biological systems. The key to success, however, is in combining new visions with strong theoretical foundations and understanding the needs of practical implementations. The Department of Signal Processing in Tampere University of Technology (TUT) strives to offer adequate education and research environment to meet the challenges of the dynamically changing field by updating the curriculum and engaging in timely research topics. The Department offers courses and conducts research in the areas of speech and audio (audio content understanding and voice conversion), spectral and algebraic techniques in digital signal processing (efficient signal representations, matrix algebra, transform methods), nonlinear signal processing, video analysis and coding, including multi view video coding, video streaming, forward error correction (FEC) and video quality; contentbased multimedia indexing and retrieval (lowlevel audio-visual descriptors, efficient indexing and query optimization), statistical modeling and compression, statistical inference for genomics, interactive multimedia technology, multimedia and data mining, health informatics, biological signal and image processing, design and implementation of digital filters and filter banks, virtual reality, perceptual user interfaces and 3D graphics, signal processing for systems biology (computational and machine learning methods for functional genomics and cell signaling, modeling and simulating complex biological phenomena), ambient multimedia and digital TV. The research work is conducted by several collaborative groups. In education some minor changes in the curriculum have been implemented in 2008 and in The Department is now responsible for Degree Programme in Signal Processing and Communications Engineering together with the Department of Communication Engineering. This will be the major source of students in the future. A new three-year project Personal Trainer has been started to transfer the best practices from the world to Tampere University of Technology to improve the throughput and the quality of the graduated students even more. The project is financed by the Centennial foundation of the Technology Industries in Finland. During the biennium the chair of Digital Audio Signal Processing was open and PhD Serkan Kiranyaz was selected to the position. The Department of Signal Processing hosts the Academy of Finland Centre of Excellence in Signal Processing ( ). The Centre involves roughly half of the researchers and most of the faculty and continues to produce high quality research papers and doctoral theses. Building on its long term cooperation with Nokia, the Department entered in 2007 into a new dimension of partnership with the world-leading industry of mobile phones, by establishing the joint Nokia-TUT Innovation Center. The Center involves researchers and faculty from several departments of TUT, in addition to Signal Processing. The Center is expected to serve as a national model of industry-academy cooperation in the future. The Center has been active in education and research during the biennium. Around postgraduate students participated a joint Mobile Imaging Course. Demola which started in 2008 is an opportunity for students to contribute to real-life innovations and an opportunity for organisations to run agile development projects with students (

4 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT Protomo is for young inventors and creators to find the next generation of digital services, products, and social practices ( The Department has also contributed to the University Alliance Finland, the co-operation between Tampere University of Technology, Tampere University and University of Jyväskylä. The Department has been especially active with one project named Statcore but there have also been other projects. The co-operation with the Helsinki University of Technology has also continued. The Finnish Funding Agency for Technology and Innovation (TEKES) launched a new way for collaboration with the most important research and development partners in Finland, the network of Strategic Centers for Science, Technology and Innovation. This solution offers top research institutes and businesses a new way of engaging in close, long-term cooperation. There are six Centers. The Department has been active with Information and communication industry and services: TIVIT Ltd. By our strategy the Department strives to increase the wide international co-operation. The Tampere International Center for Signal Processing (TICSP) is such a natural part of the Department that one almost forgets to mention it. TICSP has hosted visiting scholars and students from 35 countries making the Department stand out in internationalization in Finland. The visitors engage in their research interests together with other researchers and graduate students from TUT. The Academy of Finland has also approved the Department s grant proposal to host world renowned professors within its Finnish Distinguished Program, FiDiPro. Professor Edward Delp from Purdue University has taken up his new post at the Department. Professor Stuart Kauffman from University of Calgary, Kanada has also taken up his appointment from the beginning of the year They have been collaborating with several research groups while staying in TUT and 21 in The number of 21 doctors is a record in TUT. The number of Master s Degrees, was 26 in 2008 and 27 in Researchers exchange in the Department has been growing steadily in the past few years and has exceeded 70 man-years in The Department published over 300 articles in national and international journal and conference proceedings. Psycon Oy made a survey of the well-being of the personnel in 2008 in Tampere University of Technology. The Department of Signal Processing was among the best within the university. Besides the high productivity, the wellbeing of the personnel seems to be good, too. Finally, I would like to thank our students and researchers for their good work, our staff for their hard work, tolerance and patience, and most of all, our faculty for their genuine dedication to their research students and the Department. Ari Visa Head, Department of Signal Processing The Department of Signal Processing coordinates the National Node for International Neuroinformatics (INCF). The Department plays a key role in this important research field nationally and internationally. Three new European Community financed research projects (Mobile 3DTV, ESTOOLS and Hercules-B) have been started during the biennium. Keeping with its tradition, the Department contributed a great deal to the doctorate degrees in TUT by graduating 11 doctors of technology in

5 5 PERSONNEL PERSONNEL Professors Visa Ari, Head of the Institute, MMDM (Multimedia and Data Mining Group) Astola Jaakko, Vice Head of the Institute, Director of TICSP (Tampere International Center for Signal Processing) and SPAG (Signal Processing Algorithm Group) Defee Ireneusz, MM (Multimedia group) Egiazarian Karen, TRANS (Transforms and Spectral Techniques Group) Gabbouj Moncef, IVA (Image and Video Analysis Group) Klapuri Anssi, ARG (Audio Research Group) Ruotsalainen Ulla, M2OBSI (Methods and Models for Biological Signals and Images) Saramäki Tapio, FILT (Digital Filtering group) Tabus Ioan, STAT (Statistical Inference for Genomics) Yli-Harja Olli, CSB (Computational and Systems Biology Research Group) Rissanen Jorma, Professor Emeritus, STAT Teaching Faculty Värri Alpo, Adjunct Professor, SSSAG (Sleep and Sensory Signal Analysis group) Aho Tommi, Assistant Hirvonen Petri, Assistant, MM Huttunen Heikki, Lecturer, CSB Kesseli Juha, Assistant Koivuluoma Mikko, Assistant, SSSAG Koppinen Konsta, Lecturer, ARG Lähdesmäki Harri, Assistant Professor, CSB Niemistö Antti Assistant Parviainen Mikko, Assistant, MMDM Peltonen Sari, Assistant Professor, M2OBSI Sanches Ribeiro Andre, Assistant Professor. CSB Administration Ruotsalainen Pirkko, Development Manager Peltonen Juha, Laboratory Manager Ahonen-Lehmus Maarit, Secretary Järnström Kirsi, Secretary Kulmala Hannele Secretary Larmila Virve, Secretary Parviainen Taina, Secretary Support Staff Jokela Pentti, Laboratory Master Kuisma Tommi, System Adminstrator Lanu Sami, System Adminstrator Pärssinen Jari, System Adminstrator Orava Antti, IT Research Assistant FiDiPro Professors Delp Edward Kauffman Stuart Academy Research Fellows Giurcaneau Ciprian Doru Linne Marja-Leena Adjunct Professors Kiranyaz Serkan Lamminen Heikki Lugmayr Artur Senior Researchers Acimovic Jugoslava Ahdesmäki Miika Autio Reija Betser Michae Bregovic Robert Danielian Eduard Dumitrescu Bogdan Ferenets Rain Gotchev Atanas Healy Shannon Ince Turker Katkovnik Vladimir Koivisto Pertti Manninen Tiina Mikkonen Jarno Niiranen Samuli Nykter Matti Paliy Dmitriy Rakkolainen Ismo Rautajoki Kirsi Rezaei Mehdi Roos Christophe Ryabko Boris Stankovic Radomir Tohka Jussi Yaroslavsky Leonid Yli-Kaakinen Juha You Junyong Researchers Aflaki Beni Payman Aho Kaisa-Leena Ahsan Muhammad Ala-Kleemola Timo Autio Reija Barna Laurentiu Bazhyna Andriy Bhattacharya Mrinmoy Bilcu Beatrice Birinci Murat Boev Atanas

6 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT Calonaci Riccardo Chen Ying Dabov Kostadin Dai Xiaofeng Danielyan Aram Elyamany Abdelmoneim Noha Farinha Ricardo Foi Alessandro Georgiev Mihail Ghido Florin Golebiowski Piotr Gomez Herrero German Guldogan Esin Happonen Antti Hategan Andrea Heittola Toni Helander Elina Helén Marko Hituri Katri Hornsby Adrian Hulkkonen Jenni Intosalmi Jukka Joachimiak Michal Jumisko-Pyykkö Satu Junnila Sakari Juslin Anu Jylhä Juha Kauppi Jukka-Pekka Kauppila Jarmo Kerminen Riitta Kondrad Lukasz Kong Lingjia Korhonen Teemu Larjo Antti Laurila Kirsti Lehto Raija Li Jin Liski Antti Liu Chenghao Magadan Mendez Margarita Mäkitalo Markku Makkonen Jarmo Malamal Vadakital Vinod Mesaros Annamaria Migukin Artem Mikkonen Tomi Minasyan Susanna Niemi Jari Nikhil, Nikhil Norkin Andrey Oksanen Mikko Orpana Janne Partio Mari Pasanen Olli Paulus Jouni Perälä Henna Pertilä Pasi Pettinen Antti Pirinen Ossi Pirinen Tuomo Pogosova, Anait Pölönen Harri Pölönen Harri Popa Victor Rajala Tiina Rambla Lop Belen Razavi Alizera Reza Md Taslim Ruotsalainen Marja Rus Carol Rusanovskyy Dmytro Ruusuvuori Pekka Ryynänen Matti Saarinen Antti Sandström Saana Selinummi Jyrki Seppälä Jenni Silen Hanna Smolander Olli-Pekka Sorokin Harri Stankovic Stanislav Suominen Pertti Teppola Heidi Tervo Sakari Toivari Eeva Tuna Uygar Uhlmann Stefan Uzunov Vladislav Vihonen Juho Virtanen Tuomas Weitzel Mandy Yli-Hietanen Jari Ylipää Antti Yuan Jirui Zhang Cixun Zhao Lu Zhong Daidi Research Assistants Ahoniemi Marianne Äijö Tarmo Akbarian Azar Arezou Annala Matti Antikainen Aku Astola Helena Avdouevski, Ivan Bahrami Rad Ali Barseghyan Yuri Brajkovic Ilija Chen Weiwei Chowdhury Sharif Cricri Francesco Dadkhahi Hamid Dos Santos Alves David Erkkilä Timo Farhan Muhammad Fernandez Diaz Ana Forsell Vili Gong Xiao Hahne Lauri Haikonen Satu Häkkinen Antti Harju Manu Havela Riikka

7 7 PERSONNEL Häyrynen Jyrki Heikkilä Lasse Helin Olli Hiekkanen Antti Hollosi Danilo Holm Mika Homescu Andrei Järvenpää Laura Ji Maosheng Jin Lina Kalliokoski Heli Karjalainen Teemu Kemper Stefan Kemppi Mika Keskinen Anne Kivinen Virpi Koistinen Mika Korpelainen Tomi Koskimäki Sami Koskinen Marko Kuoppala Vesa Kyronlahti Petteri Leinonen Kalle Leppänen Mari Li Xian Lihavainen Eero Liu Yang Lloyd-Price Jason Loukiala Antti Löytynoja Antti Mäkelä Jarno Mäkinen Toni Mannerström Henrik Manninen Tapio Matikainen Juha Matthes Dirk Mikkola Maija Moradi Ramin Mozola Ivan Muttilainen Lasse Myllymäki Mikko Myllys Henna Nihtilä Tomi Nihtilä Tomi Nikunen Joonas Oinonen Hannu Pajula Juha Pekkarinen Jarkko Pepe, Antonietta Poikela Maija Pukkila Heidi Pulkkinen Jenni Qasim Ahmad Rantala Jarno Raunio Kalle Reyman Simon Roininen Mikko Ruotsalainen Antti Rutanen Kalle Ryynänen Jari-Pekka Sarbu Septimia Sarjala Anni Seppälä Janne Seppänen Mari Smirnov Sergey Tabus Vlad Tanaskovic Marko Tikanmäki Antti Tuomisto Lauri Utriainen Timo Väilä Minna Väisänen Ville Välimäki Mikko Venäläinen Ilkka Vorne Pekka Zhang Bowen Zhu Haibo Zhu Xizhi Zou Jun Interns Armas Cabezudo Luis Gonzalez Blancou Leire Meija Banuelos Mario Mukha Aliaksei Pathirage Don Janithapri Tsirakelis Perikilis Wozniak Mariusz

8 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT EDUCATION The Department of Signal Processing gives education in undergraduate and graduate levels aiming at the degrees of Bachelor of Science (B.Sc.), Master of Science (M.Sc.), Licentiate of Technology (Lic. Tech.) and Doctor of Technology (Dr. Tech.). The B.Sc. degree has only existed in our university since August The students do not consider this degree other than an intermediate step and therefore only a few B.Sc.s have yet graduated. The education offered by the department is more targeted to the advanced students than to the beginners. The first year students in Information Technology have the course Methods of signal Processing and another compulsory course Applications of signal processing is targeted for the second year students. The rest of the courses are mostly intended for those who include Signal processing and Multimedia as their main or side subject in their B.Sc. degree or to those who include Signal processing, Multimedia or Computational systems biology as their major or minor for their M.Sc. degree. The graduate courses are usually seminars in which the students prepare presentations to fellow students about a specific topic area after the introductory lectures of the teacher. The list of courses offered by the department is rather long and there are multiple choices to focus on. For example, the M.Sc. student can specialize in image and video processing, speech and audio signal processing, medical image and signal processing or general signal processing methods. Additionally, the students are offered minors in learning and intelligent systems and language technology. The illustration below shows the development of educational results along years in the institute. The M.Sc. degrees topped in 2003 being 32 whereas the Dr.Tech. degrees made the university record in 2009: 21! The amount of credits given of courses passed has been fluctuating in this decade as shown. A project to improve the personal guidance of the undergraduate students of the department was started in Fall The purpose is to interview every majoring student of the department and develop them to excellence in a personalized way.

9 9 COURSES GIVEN IN 2008 COURSES GIVEN IN 2008 SGN-1107 Introductory Signal Processing, 4 cr, Prof. Prof. Karen Eguiazarian, Atanas Gotchev SGN-2056 Digital Linear Filtering II, 4 cr, Prof. Tapio Saramäki SGN-2156 System Level DSP Algorithms, 4 cr, Prof. Tapio Saramäki SGN-1200 SGN-1200 Signaalinkäsittelyn menetelmät Signal Processing Methods, 4 cr, Heikki Huttunen SGN-1250 Signaalinkäsittelyn sovellukset SGN-1250 Signal Processing Applications, 4 cr, Heikki Huttunen, (Juha Kesseli / kesä) SGN-1600 SGN-1600 SGN-1650 SGN-1650 SGN-1656 SGN-1700 SGN-1700 SGN-1706 SGN-1970 SGN-1970 Signaalinkäsittelyn ja multimedian työkurssi Signal Processing and Multimedia Laboratory, 5 cr, Mikko Koivuluoma Signaalinkäsittelyn työkurssi Signal Processing Laboratory, 5 cr Signal Processing Laboratory, 5 cr Signaalinkäsittelyn projektityö Signal Processing Project, 5-8 cr, Sari Peltonen Signal Processing Project, 5-8 cr, Sari Peltonen Signaalinkäsittelyn kandidaattiseminaari Bachelor s Seminar in Signal Processing, 0 cr, Heikki Huttunen SGN-1980 Signaalinkäsittelyn diplomityöseminaari SGN-1980 Signal Processing Thesis Seminar, 1 cr, Alpo Värri SGN-1986 Signal Processing Thesis Seminar, 1 cr, Alpo Värri SGN-1990 Signaalinkäsittelyn diplomityöseminaariesitys SGN-1990 Signal Processing Thesis Seminar Presentation, 0 cr, Alpo Värri SGN-1996 SGN-2010 SGN-2010 SGN-2016 Signal Processing Thesis Seminar Presentation, 0 cr, Alpo Värri Digitaalinen lineaarinen suodatus I Digital Linear Filtering I, 5 cr, Raija Lehto, Prof. Tapio Saramäki Digital Linear Filtering I, 5 cr, Prof. Tapio Saramäki SGN-2206 SGN-2306 SGN-2406 SGN-2500 SGN-2500 SGN-2506 SGN-2556 SGN-2706 SGN-2806 SGN-3010 SGN-3010 SGN-3016 SGN-3056 SGN-3106 SGN-3156 SGN-3506 SGN-3636 Adaptive Signal Processing, 5 cr, Prof. Ioan Tabus Signal Compression, 5 cr, Prof. Ioan Tabus Spectrum Estimation and Array Signal Processing, 4 cr, Prof. Ioan Tabus Johdatus hahmontunnistukseen Introduction to Pattern Recognition, 4 cr, Prof. Ulla Ruotsalainen, Jussi Tohka Introduction to Pattern Recognition, 4 cr, Prof. Ulla Ruotsalainen, Jussi Tohka, Jari Niemi Pattern Recognition, 5 cr, Prof. Ulla Ruotsalainen, Prof. Ari Visa Nonlinear Signal Processing, 5 cr, Prof. Moncef Gabbouj, Sari Peltonen Neural Computation, 5 cr, Prof. Ari Visa Digitaalinen kuvankäsittely I Digital Image Processing I, 5 cr, Sari Peltonen Digital Image Processing I, 5 cr, Prof. Moncef Gabbouj, Serkan Kiranyaz Digital Image Processing II, 5 cr, Prof. Karen Eguiazarian Digital Video Processing, 4 cr, Roberto Castagno, Prof. Moncef Gabbouj Video Compression, 4 cr, Prof. Moncef Gabbouj, Imed Bouazizi Introduction to Medical Image Processing, 4 cr, Prof. Ulla Ruotsalainen Human Visual System, 3 cr, Heikki Lamminen

10 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT SGN-3906 Graduate Seminar on Medical Image Processing, 5 cr, Prof. Ulla Ruotsalainen SGN-6236 Modeling Techniques for Stochastic Gene Regulatory Networks, 3 cr, Andre Sanches Ribeiro SGN-4010 SGN-4010 SGN-4051 SGN-4051 SGN-4106 Puheenkäsittelyn menetelmät Speech Processing Methods, 2 cr, Konsta Koppinen Puheen koodaus Speech Coding, 4 cr, Konsta Koppinen Speech Recognition, 5 cr, Konsta Koppinen SGN-6307 SGN-6457 SGN-6906 Complex Systems I, 3 cr, Prof. Olli Yli-Harja, Juha Kesseli Computational Models in Complex Systems, 5 cr, Prof. Olli Yli-Harja, Juha Kesseli Seminar on Signal Processing for Systems Biology, 2-3 cr, Prof. Olli Yli-Harja SGN-4200 SGN-4200 Digitaalinen audio Digital Audio, 5 cr, Konsta Koppinen, T uomas Virtanen SGN-4507 Speech Recognition Laboratory, 3 cr, Konsta Koppinen SGN-5016 Multimedia Signal Processing, 4 cr, Prof. Ireneusz Defee SGN-5106 Multimedia Systems and Communications, 4 cr, Prof. Ireneusz Defee SGN-9016 SGN-9106 SGN-9206 SGN-9306 Orientation to Postgraduate Studies, 3 cr, Prof. Moncef Gabbouj Signal Processing Graduate Seminar I, 3-8 cr, Prof. Jaakko Astola Signal Processing Graduate Seminar II, 3-8 cr, Prof. Moncef Gabbouj, Anssi Klapuri Signal Processing Graduate Seminar III, 3-8 cr, Prof. Ioan Tabus SGN-5200 SGN-5200 Multimedia joukkoviestimissä Broadcast Multimedia, 3 cr, Prof. Ireneusz Defee, Artur Lugmayr SGN-9406 Signal Processing Graduate Seminar IV, 3-8 cr, Prof. Olli Yli- Harja SGN-5406 SGN-5706 Virtual Reality, 5 cr, Artur Lugmayr, Ismo Rakkolainen Multimedia Project, 5-8 cr, Prof. Ireneusz Defee SGN-5806 Wireless Ambient Multimedia, 5 cr, Artur Lugmayr SGN-5856 Media Technologies Seminar, 5 cr, Prof. Ireneusz Defee SGN-9506 Graduate Research Seminar, 5-8 cr, Prof. Jaakko Astola, Sari Peltonen SGN-9906 SGN-9916 Short International Course in Signal Processing, 1-5 cr, Artur Lugmayr Extensive International Course in Signal Processing, 6-10 cr, Prof. Jaakko Astola SGN-5906 Virtual Reality Seminar, 5 cr, Artur Lugmayr, Ismo Rakkolainen SGN-6056 Introduction to Computational Systems Biology, 3 cr, Marja- Leena Linne SGN-6106 Computational Systems Biology I, 5 cr, Prof Olli Yli-Harja SGN-6156 SGN-6206 Computational Systems Biology II, 5 cr, Prof Olli Yli-Harja Genomic Signal Processing, 5 cr, Prof. Ioan Tabus

11 11 COURSES GIVEN IN 2009 COURSES GIVEN IN 2009 SGN-1107 Introductory Signal Processing, 4 cr, Prof. Prof. Karen Eguiazarian SGN-1156 Signal Processing Techniques, 4 cr, Prof. Karen Eguiazarian SGN-1200 SGN-1200 Signaalinkäsittelyn menetelmät Signal Processing Methods, 4 cr, Heikki Huttunen, (Konsta Koppinen / kesä) SGN-1250 Signaalinkäsittelyn sovellukset SGN-1250 Signal Processing Applications, 4 cr, Heikki Huttunen, (Juha Kesseli / kesä) SGN-1650 Signaalinkäsittelyn työkurssi SGN-1650 Signal Processing Laboratory, 5 cr, Mikko Parviainen SGN-1656 Signal Processing Laboratory, 5 cr, Mikko Parviainen SGN-2306 SGN-2406 SGN-2506 SGN-2706 SGN-2806 SGN-3010 SGN-3010 SGN-3016 Signal Compression, 5 cr, Prof. Ioan Tabus Spectrum Estimation and Array Signal Processing, 4 cr, Prof. Ioan Tabus Introduction to Pattern Recognition, 4 cr, Prof. Ulla Ruotsalainen, Jussi Tohka Nonlinear Signal Processing, 5 cr, Sari Peltonen Neural Computation, 5 cr, Prof. Ari Visa Digitaalinen kuvankäsittely I Digital Image Processing I, 5 cr, Sari Peltonen Digital Image Processing I, 5 cr, Prof. Moncef Gabbouj, Serkan Kiranyaz SGN-1706 Signal Processing Project, 5-8 cr, Sari Peltonen SGN-3106 Digital Video Processing, 4 cr, Prof. Moncef Gabbouj SGN-1970 SGN-1970 Signaalinkäsittelyn kandidaattiseminaari Bachelor's Seminar in Signal Processing, 0 cr, Heikki Huttunen, Konsta Koppinen SGN-1980 Signaalinkäsittelyn diplomityöseminaari SGN-1980 Signal Processing Thesis Seminar, 1 cr, Alpo Värri SGN-1986 Signal Processing Thesis Seminar, 1 cr, Alpo Värri SGN-1990 Signaalinkäsittelyn diplomityöseminaariesitys SGN-1990 Signal Processing Thesis Seminar Presentation, 0 cr, Alpo Värri SGN-1996 Signal Processing Thesis Seminar Presentation, 0 cr, Alpo Värri SGN-3507 SGN-3637 Introduction to Medical Image Processing, 5 cr, Prof. Ulla Ruotsalainen Human visual system, 4-5 cr, Heikki Lamminen SGN-4010 Puheenkäsittelyn menetelmät, 2 cr, Konsta Koppinen SGN-4200 SGN-4200 Digitaalinen audio Digital Audio, 5 cr, Tuomas Virtanen SGN-4226 Digital Audio Processing and Analysis, 5 cr, Serkan Kiranyaz SGN-5200 SGN-5200 Multimedia joukkoviestimissä Broadcast Multimedia, 3 cr, Prof. Ireneusz Defee, Adrian Hornsby, Artur Lugmayr SGN-2010 SGN-2010 SGN-2016 SGN-2206 Digitaalinen lineaarinen suodatus I Digital Linear Filtering I, 5 cr, Raija Lehto Digital Linear Filtering I, 5 cr, Robert Bregovic, Prof. Tapio Saramäki Adaptive Signal Processing, 5 CR, Prof. Ioan Tabus SGN-5406 SGN-5706 Virtual Reality, 5 cr, Ismo Rakkolainen Multimedia Project, 5-8 cr, Prof. Ireneusz Defee SGN-5806 Wireless Ambient Multimedia, 5 cr, Artur Lugmayr, Samuli Niiranen

12 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT SGN-5857 Multimedia Graduate Seminar, 5 cr, Prof. Ireneusz Defee, Prof. Moncef Gabbouj, Artur Lugmayr SGN-5906 Virtual Reality Seminar, 5 cr, Artur Lugmayr, Ismo Rakkolainen SGN-6056 Introduction to Computational Systems Biology, 3 cr, Marja- Leena Linne SGN-6106 Computational Systems Biology I, 5 cr, Prof. Olli Yli-Harja SGN-6156 Computational Systems Biology II, 5 cr, Prof Olli Yli-Harja SGN-6166 Introduction to R programming, 3 cr, Tommi Aho SGN-6186 SGN-6206 SGN-6236 SGN-6457 SGN-6906 SGN-9016 SGN-9106 SGN-9206 SGN-9306 SGN-9406 SGN-9906 SGN-6057 Mathematical Modeling of Cellular Systems, 5 cr, Tiina Manninen Genomic Signal Processing, 5 cr, Prof. Ioan Tabus Modeling Techniques for Stochastic Gene Regulatory Networks, 3 cr, Andre Sanches Ribeiro Computational Models in Complex Systems, 5 cr, Juha Kesseli Seminar on Signal Processing for Systems Biology, 2-3 cr, Reija Autio, Prof. Olli Yli-Harja Orientation to Postgraduate Studies, 3 cr, Prof. Jaakko Astola, Prof. Moncef Gabbouj Signal Processing Graduate Seminar I, 3-8 cr, Prof. Jaakko Astola Signal Processing Graduate Seminar II, 3-8 cr, Prof. Moncef Gabbouj, Anssi Klapuri Signal Processing Graduate Seminar III, 3-8 cr, Prof. Ioan Tabus Signal Processing Graduate Seminar IV, 3-8 cr, Antti Niemistö Short International Course in Signal Processing, 1-5 cr, Artur Lugmayr Introduction to Cell and Molecular Biology, 3 cr, Marja-Leena Linne

13 13 THESES THESES Bachelor s Degrees Topi Santakivi, , Objektiivinen kuvan laadun arviointi, Supervisor: Lecturer Heikki Huttunen Tapio Manninen, , Iiris biometrisena tunnisteena, Supervisor: Lecturer Heikki Huttunen Tarmo Äijö, , Gaussin prosessit regressioanalyysissä, Supervisor: Lecturer Heikki Huttunen Mikko Roininen, , Musiikin aikaskaalaus, Supervisor: Lecturer Heikki Huttunen Juha Kalamies, , Ihonväritunnistus, Supervisor: Lecturer Heikki Huttunen Kyösti Herrala, , Kasvojen paikannus, Supervisor: Lecturer Heikki Huttunen Virpi Kivinen, , Geeniekspressio- ja kopiolukumittaukset ruoansulatuskanavan syövillä, Supervisor: Lecturer Heikki Huttunen Lauri Soini, , Lineaarisen Kalmansuotimen käyttö paikannuksessa, Supervisor: Lecturer Heikki Huttunen Antti Häkkinen, , DNA-sekvenssien etsiminen ja löydösten merkitysten analysointi, Supervisor: Lecturer Heikki Huttunen Jyrki Häyrynen, , Tiedon piilottaminen kuviin, Supervisor: Lecturer Heikki Huttunen Mikko Loimusalo, , CANväylämittausten ja analogisten mittausten yhdistämismahdollisuudet, Supervisor: Lecturer Heikki Huttunen Jarkko Pekkarinen, , PNGkuvaformaatti ja sen tulevaisuus, Supervisor: Lecturer Heikki Huttunen Timo Salokas, , Microsoftin DirectXtekniikka ja antialiasointi, Supervisor: Lecturer Heikki Huttunen Pasi Sillanpää, , Sormenjälki biometrisenä tunnisteena, Supervisor: Lecturer Heikki Huttunen Juho Blankenstein, , Mittaussignaalin pakkaaminen, selvitys pakkausalgoritmeista, Supervisor: Konsta Koppinen Lauri Hahne, , Näytönohjainavusteinen digitaalisen kuvan koon muuttaminen hyödyntäen Lanczos-suodatinta ja CUDA-rajapintaa, Supervisor: Konsta Koppinen Ilkka Hulkko, , Taajuuden mittaus painesignaalista, Supervisor: Konsta Koppinen Miska Kyrönlahti, , Radiolähetteiden parametrisointi digitaalisen tutkaan hakeutuvan ohjuksen hakupään signaalista, Supervisor: Konsta Koppinen Lasse Muttilainen, , Puoliaktiivisen ja aktiivisen hakupään vastatoimenpiteet, Supervisor: Konsta Koppinen Eetu Ojanen, , Signaalin ennustaminen Kalman-suotimella, Supervisor: Konsta Koppinen Joni Pahlama, , Sinimallinnukseen perustuva musiikin synteesi, Supervisor: Konsta Koppinen Diploma Theses Antti Koponen, , Sektoriloiston värirajojen automaattinen tunnistus, Supervisors: Prof. Jukka Lekkala and Assistant Prof. Sari Peltonen Ahmad Qasim, , ESG Data Generator and Interactive Browser for Mobile TV, Supervisors: Prof. Irek Defee and Senior Researcher Artur Lugmayr Henna Myllys, , Menetelmä kineettisten parametrien biologisten jakaumien ratkaisemiseksi PET-sinogrammiaikasarjasta, Supervisors: Prof. Keijo Ruohonen and Prof. Ulla Ruotsalainen, Antti Ylipää , High-throughput Identification of DNA Copy Number Aberrations, Supervisors: Prof. Olli Yli-Harja and Dr.Tech. Matti Nykter, Sampo Meklin, , Test Process Improvement Base on Analysed Fault Reports, Supervisors: Prof. Irek Defée and Docent. Mika Katara Xinghan Luo, , Algorithms for Face and Facial Feature Detection, Supervisors: Senior researcher Atanas Gotchev, Prof. Karen Egiazarian and Prof. Jörn Östermann Jarmo Kauppila, , Metallinilmaisinportin testausympäristö ja sen soveltaminen objektin tunnistamiseen, Supervisors: Prof. Ari Visa and Prof. Jukka Vanhala

14 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT Mikko Myllymäki, , Voice activity detection in the presence of breathing noise, Supervisors: Prof. Anssi Klapuri and Tuomas Virtanen Henna Perälä, , Tutkakaikulähteiden paikallistaminen, Supervisors: Prof. Ari Visa and Prof. Irek Defee Jarkko Rouhe, , Kuljettajan ajotapaindeksin määritys sumealla logiikalla, Supervisors: Prof. Jouko Halttunen, Prof. Ari Visa and M.Sc. Juha Laitsaari Mikko Tiainen, , Automaattinen solulaskenta Medicel Explorer kasvatusympäristössä, Supervisors: Prof. Olli Yliharja and M.Sc. Jarno Mäkinen (Medicel Oy) Yugar Tuna, , Cosine Domain Gap- Filling for the PET Sinograms, Supervisors: Prof. Ulla Ruotsalainen and Assistant Prof. Sari Peltonen Volker Bruns, , Acceleration of a JPEG2000 Coder by Outsourcing Arithmetically Intensive Computations to a GPU, Supervisors: Senioir Researcher. Artur Lugmayr and M.Sc. Heiko Sparenberg Simon Reymann and Stefan Kemper, AmbiNet A Lightweight Development Framework for Ambient Application Design, Supervisors: Senior Researcher. Artur Lugmayr and Prof. Pirkko Oittinen Tommi Määttä, , Multi-view capture of human shape, stucture and motion, Supervisors: Prof. Irek Defee and Dr.Tech. Aki Härmä (Philips Research Laboratories) Antonietta Pepe, , Automatic Shape Asymmetry Analysis of Human Cerebral Hemispheres in Schizophrenia based on MRI, Supervisors: Prof. Ulla Ruotsalainen and M.Sc. Lu Zhao Arif Zuberi, , Towards Face Recognition for Multimedia Retrieval Applications, Supervisors: Prof. Moncef Gabbouj and M.Sc. Honglei Zhang (Nokia/ Devices) Ricardo Farinha, , Segmentation of Striatal Brain Structures from High Resolution PET Images, Supervisors: Prof. Ulla Ruotsalainen and Senior Researcher. Jussi Tohka Pablo Roman Humanes, , Movement tracking for interaction with a virtual character, Supervisors: Senior Researcher. Artur Lugmayr and Prof. Irek Defee Muhammad Ahsan, , Design of Optimum Linear-Phase FIR Filters with a Modified Implementation of the Remez Multiple Exchange Algorithm, Supervisors: Prof. Tapio Saramäki and Prof. Markku Renfors Toni Mäkinen, , Impulssimaisten äänilähteiden havainnointi ja suuntimen mikrofoniasetelman avulla, Supervisors: Prof. Anssi Klapuri and Researcher Pasi Pertilä Francesco Cricri, , Media Mixing and Inter-Client Synchronization for Mobile Virtual TV-Room, Supervisors: Prof. Moncef Gabbouj and M.Sc. Miska Hannuksela (NRC) Roger Mallol Parera, , Computational tool for strain design: Maximizing yields in metabolic systems, Supervisors: Prof. Olli Yli-Harja and Assistant Tommi Aho Taslim Reza, , Vignetting artifact reduction in a efficient way for Digital Camera image,, Supervisors : Prof. Jari Hyttinen and Prof. Ari Visa Timo Erkkilä, , Empirical Mixture Modeling for Detecting Differential Expression in High-Throughput Measurements, Supervisors: Dr.Tech. Harri Lähdesmäki and Prof. Olli Yli- Harja Hannu Koivuniemi, , Design Principles for Renewing the Communication Network of an Energy Company, Supervisors: Prof. Markku Renfors, Assistant Prof. Ari Asp, Senior Researchr Alpo Värri ja Sauli Antila (Vattenfall Verkko Oy) Xilin Wang, , Chromosome extraction in microscope images, Supervisors: Prof. Irek Defee and Lecturer Heikki Huttunen Hannu Oinonen, , Bioidentification Based on Matching of Retinal Vessels, Supervisors: Docent. Heikki Lamminen and M.Sc. Pekka Ruusuvuori Ville Väisänen, , An Approach to Enhanced Fidelity of Airborne Radar Site-specific Simulation, Supervisors: Prof. Ari Visa and Prof. Jaakko Astola Antti Löytynoja, , Partikkelisuotimeen perustuva reaaliaikainen puhujan paikannus Pure Data -ohjelmistolla, Supervisor: Prof. Anssi Klapuri Teemu Markkanen, , Analysis of Internet Audio-Visual Services for Mobile Media Player Usage, Supervisor: Prof. Irek Defee

15 15 THESES Manjula Karunakaran, , Adaptive Fusing of Multiple Images in Mobile Imaging Playground, Supervisor: Prof. Karen Egiazarian Anssi Salonen, , Conformational Analysis of Sphingolipids with Self-Organizing Maps, Supervisor: Prof. Olli Yli-Harja Jun Zou, , Low bit-rate compression for speech and audio coding, Supervisor: Prof. Ioan Tabus Meri Kailanto, , Yhteisöllinen verkkopalvelujen laadukkuuskriteerit, Supervisor: Prof. Irek Defee Veronica Schirru, , Biometric Authentication System Based on Fuzzy Vault and Tree-Structured Haar Transform, Supervisor: Prof. Karen Egiazarian Pasi Pyykkönen, , Kamerapohjaisten havainnointimenetelmien yhdistäminen ihmisten tunnistamiseksi työkoneen ympäristössä, Supervisor: Heikki Huttunen Antti Vilkko, , Automatic Detection of Power Consumption Problems in Smartphones, Supervisor: Prof. Ari Visa Muhammed Hanif, , 3D Reconstruction of Focused Flocs from Two Views, Supervisor: Prof. Ari Visa Jenni Pulkkinen, , Applications of Multi-dimensional Particle Swarm Optimization, Supervisor: Prof. Moncef Gabbouj Preethi Sundaresan, , Comparative Study of Two Different Mobile Architectures from an Audio Perspective, Supervisor: Prof. Irek Defee Andrei Homescu, , Statistical Models and Entropy Coding Methodss for Short Sequences, Supervisor: Prof. Ioan Tabus Septimia Sarbu, , Low bit rate vector quantization based on shells of Golay codes for audio and speech coding, Supervisor: Prof. Ioan Tabus Tarmo Äijö, , Learning the Structure of an in Vitro Gene Regulatory Network Using Gaussian Processes, Supervisor: Harri Lähdesmäki Ivan Avdouevski, , Committee Machine-based Method for User Activity Recognition, Supervisor: Prof. Ari Visa Sharif Chowdhury, , Tracking Cells and Vesicles in Microscope Images, Supervisor: Prof. Olli Yli-Harja Ulla-Maria Kovalainen, , Sisällön suojaaminen DVB-H Standardissa, Supervisor: Prof. Irek Defee Ana Fernandez Diaz, , Automatic Correction of Artifacts in the EEG: Impact on Indexes of Functional Connectivity in the Human Brain, Supervisor: Prof. Karen Egiazarian Jyrki Kajasrinne, , Paperin näytteenotto digitaalikuvien avulla, Supervisor: Prof. Ari Visa Antti Loukiala, , Gap-Filling Methods for the ClearPETTM Sinograms, Supervisor: Prof. Ulla Ruotsalainen Tapio Manninen, , Computer Vision Aided Print Pattern Generation in Inkjet Printed Electronics, Supervisor: Prof. Ari Visa Kalle Raunio, , GPU Assisted Visualization on Autostereoscopic 3D Displays, Supervisor: Atanas Gotchev Ilkka Venäläinen, , Model-based Interpretation for Long-term Response of Pulsed Doppler Radar, Supervisor: Prof. Ari Visa Jani Viitala, , Impedanssikardiografian ja pulssiaaltoanalyysin mittausdatan yhdistäminen ja esikäsittely sekä tietoturvallisen tietokannan toteutus DYNAMIC-tutkimuksessa, Supervisor: Prof. Ulla Ruotsalainen Doctoral Theses Marco Carli, "Perceptual Aspects in Data Hiding", on January 14, Opponents: Dr. Mauro Barni, University of Sienna, Italy and Dr. David Gevorkian, Nokia Research Center, Tampere, Finland. Custos: Prof. Jaakko Astola. Laurentiu Barna, "Acquisition Systems and Analysis Methods for Human Originated Signals", on February 15,2008. Opponent: Dr. Kaj Lindecrantz, Högskolan I Boras, Sweden. Custos: Adjunct Professor Alpo Värri. Daidi Zhong, "Image Database Retrieval Methods based on Feature Histograms'", on May 23, Opponents: Prof. Dietrich Paulus, Universität Koblenz-Landau, Germany and Ph.D. Adrian Bors, University of York, Great Britan. Custos: Prof. Irek Defee.

16 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT Mehdi Rezaei, "Advances on Video Coding Algorithms for Streaming Applications", on May 24, Opponents: Prof. Olli Siiven, University of Oulu, Finland and Dr. Roberto Castagno, Nokia Mobile Phones, Tampere, Finland, Custos: Prof. Moncef Gabbouj. Juha Iso-Sipilä, "Design and Implementation of a Speaker-Independent Voice Dialing System: A Multi-Lingual Approach", on April 18, Opponents: Assoc. prof. Khaled Assaleh, American University of Sharjah, United Arab Emirates and Ph.D. Mikko Kurimo, Helsinki University of Technology, Adaptive Informatics Research Centre, Finland. Custos: Prof. Moncef Gabbouj. Evgeny Krestyannikov, "Iterative reconstruction of regional tracer kinetics from projection data in brain positron emission tomography (PET)", on August 22,2008. Opponent: Prof. Johan Nuyts, Katholieke Universiteit Leuven, Belgia, Custos: Prof. Ulla Ruotsalainen. Reija Autio, "Computational Methods for High- Throughput Data Analysis in Cancer Research", on September 24,2008. Opponent: Prof. Samuel Kaski, Helsinki University of Technology, Finland. Custos: Prof. Jaakko Astola. Margarita Julia Magadan Méndez, "Signal Separation from Dynamic Data with Independent Component Analysis", on October 10,2008. Opponents: Prof. Aapo Hyvärinen, University of Helsinki, Finland and Prof. José Fonseca, Universidade Nova de Lisboa, Portugal. Custos: Prof. Ulla Ruotsalainen. Enikö Beatrice Bilcu, "Text-To-Phoneme Mapping Using Neural Networks", on October 22, Opponents: Prof. Pasi Fränti, University of Joensuu, Finland and Dr. Marco Carli, University of Roma TRE, Italy. Custos: Prof. Jaakko Astola. Tommi Lahti, "On low complexity techniques for automatic speech recognition and automatic audio content analysis", on December 1, Opponents: Prof. Reiner Creutzburg, Fachhochschule Brandenburg, Germany and Dr. Markku Turunen, University of Tampere, Finland. Custos: Prof. Jaakko Astola. Nikhil, "Knowledge Mining of Fermentative Hydrogen Processes", on December 9, Opponent: Prof. Kimmo Kaski, Helsinki University of Technology, Finland. Custos: Prof. Olli Yli-Harja. Matti Ryynänen, "Automatic Transcription of Pitch Content in Music and Selected Applications, on December 12, Opponents: Prof. Vesa Välimäki, Helsinki University of Technology, Finland and Dr. Simon Dixon, University of London, England. Custos: Prof. Anssi Klapuri. Jyrki Selinummi, "On algorithms for two and three dimensional high throughput light microscopy", on December 19, Opponent: Prof. Jussi Parkkinen, University of Joensuu, Department of Computer Science and Statistics, Finland. Custos: Prof. Olli Yli-Harja. Esin Guldogan, Improving Content-Based Image Indexing and Retrieval Performance, on January 9, Opponents: Prof. Vladimir Lukin, Kharkov Aviation Institute, Ukraine, and PhD Iivari Kunttu, Nokia, Devices R&D, Finland. Custos: Prof. Moncef Gabbouj. Antti Saarinen, Stochastic Modeling of Neuronal Excitability: Model Construction, Simulation and Parameter Estimation, on January 13, Opponent: Prof. Pétr Lansky, Academy of Sciences of the Czech Republic, Czech Republic. Custos: Prof. Olli Yli-Harja. Pasi Pertilä, Acoustic Source Localization in a Room Environment and at Moderate Distances, on January 30, Opponent: Prof. Martin Vermeer, Helsinki University of Technology, Finland. Custos: Prof. Ari Visa. Miska Hannuksela, Error-Resilient Communication Using the H.264/AVC Video Coding Standard, on March 23, Opponents: Prof. Fernando Pereira, Instituto Superior Técnico Instituto de Telecomunicacoes, Portugal, and PhD Nikolaus Färber, Fraunhofer IIS, Germany. Custos: Prof. Moncef Gabbouj. Andriy Bazhyna, Image Compression for Digital Cameras, on March 30, Opponent: Prof. Reiner Creutzburg, Fachhochschule Brandenburg, Germany. Custos: Prof. Karen Egiazarian. Tomi Mikkonen, The Ring of Graph Invariants, on May 8, Opponent: Prof. William Kocay, University of Manitoba, Canada. Custos: Prof. Jaakko Astola. Miikka Ermes, Methods for the Classification of Biosignals Applied to the Detection of Epileptiform Waveforms and to the Recognition of Physical Activity, on May 15, Opponent: Assoc. Prof. Georg Dorffner, Medical University of Vienna, Austria. Custos: Dos. Alpo Värri Jussi Virkkala, Automatic Sleep Stage Classification Using Electro-oculography, on May 20, Opponent: Prof. Piotr Durka, University of Warsaw, Poland. Custos: Dos. Alpo Värri.

17 17 THESES Raija Lehto, Synthesis Methods for Linear- Phase FIR Filters with a Piecewise-Polynomial Impulse Response, on June 2, Opponents: Prof. Paulo S. R. Diniz, Cidade Universitaria, Brasil, and Prof. Håkan Johansson, Linköping Universitet, Sweden. Custos: Prof. Tapio Saramäki. Marko Helén, Similarity Measures for Content- Based Audio Retrieval, on June 11, Opponent: Prof. Petri Toiviainen, University of Jyväskylä, Finland. Custos: Prof. Moncef Gabbouj. Antti Eronen, Signal Processing Methods for Audio Classification and Music Content Analysis, on June 25, Opponents: Prof. Petri Toiviainen, University of Jyväskylä, Finland, and PhD Geoffroy Peeters, Research & Development Department of IRCAM, France. Custos: Prof. Anssi Klapuri. Tuomo Pirinen, Confidence Scoring of Time Delay Based Direction of Arrival Estimates and a Generalization to Difference Quantities, on December 4, Opponent: Prof. Martin Vermeer, Helsinki University of Technology, Finland. Custos: Prof. Ari Visa. Antti Pettinen, On Simulation Software and Parameter Estimation for Biochemical Models, on December 8, Opponent: Prof. Maria Samsonova, Center for Advanced Studies, St. Petersburg Polytechnical University. Russia. Custos: Prof. Olli Yli-Harja. Antti Lehmussola, Image Processing for Systems Biology: Validation and Performance Evaluation Through Simulation on December 10, Opponent: PhD Carolina Wählby, Broad Insititute of Harvard and MIT, USA. Custos: Prof. Olli Yli-Harja. Juho Vihonen, Sequential Detection Applied to Line-Scan Gray Level Defect Imaging, on August 31, Opponents: Prof. Juha Röning, University of Oulu, Finland, and Prof. Björn Kruse, Linköping University, Sweden. Custos: Prof. Ari Visa. Tommi Aho, Modeling for Molecular Interaction Networks: Methodology and Applications, on October 20, Opponent: Prof. Carsten Carlberg, Université du Luxembourg, Luxembourg. Custos: Prof. Olli Yli-Harja. Andrea Hategan, Lossless compression and nonlinear modeling of protein data, on October 23, Opponents: Prof. Pasi Fränti University of Joensuu, Finland, and Assoc. Prof. Sören Forchhammer, Technical University of Denmark, Denmark. Custos: Prof. Ioan Tabus. Stanislav Stankovic, XML Based Framework for Representation of Decision Diagrams, on November 3, Opponents: Prof. Raimund Ubar, Tallinn University of Technology, Estonia, and Prof. Valeri Skliarov, University of Aveiro, Portugal. Custos: Prof. Jaakko Astola. Sakari Junnila, Modern Digital Interfaces for Personal Health Monitoring Devices, on November 27, Opponent: Prof. Jouni Isoaho, University of Turku, Finland. Custos: Dos. Alpo Värri. Dmytro Rusanovskyy, Adaptive interpolation and transform based filtering for video coding, on December 4, Opponents: Prof. Reiner Creutzburg, Fachhochschule Brandenburg, Germany, and Dr. Thomas Wedi, Panasonic R&D Center, Germany. Custos: Prof. Karen Egiazarian.

18 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT RESEARCH The Department of Signal Processing is traditionally known by its high level research. This fact was confirmed in the recent evaluation by the Academy of Finland of the scientific level of Computer Science in Finland. The full report can be found at the Academy website via Our intention is to keep this high level also in future. Research activities are organized to be performed in research groups which are rather independent. Usually each research group applies its funding, hires its personnel and carries out the research without a lot of interventions from the department management. The policy of the management to protect the groups from bureaucracy as much as possible and the possibility of the group leader to manage his/her own funding have turned out to be highly motivating factors. This independence has not, however, prevented co-operation within the department when the benefits of co-operation have been recognized by the participating groups. Tampere International Center For Signal Processing, TICSP Tampere International Center for Signal Processing, TICSP has been an essential part of the Department of Signal Processing for 12 years. During there have been over 450 visits from 28 countries to TICSP. In addition to this, TICSP has organized weekly seminars, summer courses, international workshops (e.g. in Lausanne, Florence, Vienna, Riga, Toulouse, Barcelona, Pula) and published around forty workshop proceedings and research monographs in its internationally edited TICSP series. TICSP Workshops BST Workshop TUT on March 27, BST is an informal cooperation network in switcing theory and its applications between the countries around the Baltic sea. Among others, the workshop had presentations by Raimud Ubar, Tallinn University of Technology, Department of Computer Engineering, Estonia on Low and High-Level Decision Diagrams for Test Generation and Fault Simulation in Digital Circuits and Systems, Peeter Ellervee, Tallinn University of Technology, Department of Computer Engineering, Estonia on System and Behavioural Level Synthesis for Reprogrammable Architectures, Elena Dubrova, Royal Institute of Technology (KTH), School of Information and Communication Technology, Department of Electronics, Computer and Software Systems, Stockholm, Sweden on Design of Correct, Fault-Tolerant and Secure Systems and Radomir S. Stankovic, University of Niš, Department of Computer Science, Serbia on Exploring Possibilities for Applications of Fourier Representations in Circuit Design over Reprogrammable Technological Platforms. TICSP Workshop LNLA International Workshop on Local and Non- Local Approximation in Image Processing Recently, local and non-local approximations have emerged as surprisingly powerful tools for image analysis, restoration, compression, and enhancement. The current state-of-the-art in image processing exhibits many diverse techniques, which are seemingly different but actually are intimately related through concepts such as sparsity, redundancy, compressibility, and selfsimilarity. With the intention to follow and document these latest advances, TICSP organized the first International Workshop on Local and Non-Local Approximation in Image Processing (LNLA), held in Lausanne, Switzerland August 23-24, The LNLA workshop had four keynote presentations and 24 contributed papers, reflecting the current state-of-the-art in local and non-local image processing. The workshop featured four oral sessions and many informal and fruitful discussions held during the organized lunches, breaks and reception. The LNLA 2008 Workshop was chaired by Jaakko Astola, Karen Egiazarian and Vladimir Katkovnik. Atanas Gotchev and Alessandro Foi were the technical program chairs and Robert Bregovic was the publication chair. All accepted papers were published by TICSP in its Proceedings and Reports Series. The program of the workshop can be found on TICSP Workshop LNLA 2009 Tampere International Center for Signal Processing (TICSP) has been continuously aiming at organizing high-profile international workshops on advanced and emerging topics of modern signal processing. This year TICSP organized the Second International Workshop on Local and Non-Local Approximation in Image Processing (LNLA). The workshop was held in Tuusula, Finland, on August 19-21, following the very successful first edition, held in Lausanne, Switzerland. The LNLA workshops continue the tradition of the TICSP International Workshop on Spectral Methods and Multirate Signal Processing (SMMSP), held seven times in 2001-

19 19 RESEARCH 2007, and of the TICSP International Workshop on Transforms and Filter Banks, held twice in 1998 and As with the previous workshops, the aim has been at generating stimulating interaction between people with diverse yet complementary background and expertise, emphasizing the transfer of theoretical results to practical applications, and building long-term cooperation between teams. The organizers wish to thank the co-sponsors Nokia, IEEE SP & CAS Chapter of Finland, DSP Technical Committee of IEEE Circuits and Systems Society, EURASIP, Federation of Finnish Learned Societies, and TICSP for their support, and especially the authors for their high-quality contributions. The workshop program is online at and the complete proceedings can be found on the IEEE Xplore archive. TICSP Workshop WCSB 2008 The Fifth International Workshop on Computational Systems Biology, WCSB 2008 ( hosted in Leipzig, Germany on June 11-13, 2008 brought together a large group of both biology and computing oriented researchers. Main themes of the interdisciplinary WCSB 2008 meeting included modeling and understanding biological regulatory networks, such as metabolic and genetic networks, using cellular and genome-level information. WCSB 2008 was organized by the Computational Systems Biology research group from the Tampere University of Technology, Department of Signal Proces-sing, in collaboration with the University of Leipzig and Technical University of Dortmund. The keynote speakers at the workshop were Prof. Hidde Jong, INRIA Rhone- Alpes, Grenoble, France, Prof. Stuart Kauffman, Institute for Biocomplexity and Informatics, University of Calgary, Canada, Prof. Stéphane Robin, AgroParisTech, Paris, France and Prof. Darren Wilkinson, School of Mathematics and Statistics, Newcastle University, UK. Prof. Olli Yli-Harja acted as the workshop chair. The next meeting, WCSB 2009, will be organized in Århus, Denmark. TICSP Workshop WCSB 2009 The Sixth International Workshop on Computational Systems Biology, WCSB 2009 ( hosted in Aarhus, Denmark, on June 10-12, 2009 brought together a large group of both biology and computing oriented researchers. Main themes of the interdisciplinary WCSB 2009 meeting included modeling and understanding biological networks, such as metabolic, genetic, signal transduction, and neuronal networks, using cellular and genome-level information. WCSB 2009 was organized by the Computational Systems Biology research group from Tampere University of Technology, Department of Signal Processing, in collaboration with Aarhus University and Technical University of Dortmund. It was decided to make the workshop even more influential in the field of computational systems biology by inviting five keynote speakers from top laboratories all over the world. The keynote speakers at the workshop were Erik De Schutter, Okinawa Institute of Science and Technology, Japan, Lucas Pelkmans, Swiss Federal Institute of Technology Zürich, Switzerland, Ilya Shmulevich, Institute for Systems Biology, USA, Jean- Philippe Vert, Mines ParisTech, France, and Stephen Wong, Methodist Hospital Research Institute, USA. Furthermore, Stuart Kauffman from the University of Calgary, Canada, gave a Lindhard lecture organized by Centre for Theory in Natural Science one day before the workshop as well as a dinner speech during the workshop. Olli Yli-Harja and Carsten Wiuf acted as the workshop chairs. The next meeting, WCSB 2010, will be organized in Luxembourg. TICSP Workshop WITMSE 2008 The first Workshop on Information Theoretic Methods in Science and Engineering (WITMSE) was held at the TUT on August 18-20,2008. The workshop was a unique interaction opportunity for the students and supervisors from three graduate schools: TISE (Tampere), HECSE (Helsinki), and the Research Training Group Statistical Modelling at the Technische Universität Dortmund. At the same time the workshop offered exposure to the state of the art presented by very prestigious international experts. The plenary speakers were among the founders of fundamental research in information theory at intersection with statistics: Jorma Rissanen, Imre Csizar, Andrew Barron, Sergio Verdu, and Marcelo Weinberger. The workshop dealt with hot topics in statistics, information theory, machine learning, and their applications. Latest fundamental results, trends, and open issues were presented in these promising scientific fields.for further information visit the workshop homepage

20 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT TICSP Workshop WITMSE 2009 The second Workshop on Information Theoretic Methods in Science and Engineering (WITMSE 09) was held at the Tampere University of Technology, Tampere, Finland on August 17-19, The workshop covered hot topics at the intersection of statistics, information theory, machine learning, and their applications. The invited speakers presented the latest fundamental results, trends, and open issues from all these promising scientific fields. The technical program included plenary lectures, invited oral sessions, and contributed sessions. appearance of cancer, its progression and predicting the effects of differentiation therapy on patients. The long term goal is the development of personalized medicine, where doctors can choose the best treatment for each patient. The workshop had also a strong educational drive, being intended to increase the cooperation between Tampere Graduate School in Information Science and Engineering (TISE), Helsinki Graduate School in Computer Science and Engineering (HECSE), and the Research Training Group - Statistical Modelling at the Technische Universität Dortmund. The workshop was a unique interaction opportunity for the students and supervisors from these graduate schools and at the same time it offered for attending students exposure to the state of the art presented by international experts. The plenary speakers were among the founders of fundamental research in information theory at intersection with statistics: Jorma Rissanen, Shun-ichi Amari, Bin Yu, Vladimir Vovk, and Paul Vitanyi. All accepted papers were published by the Tampere International Center for Signal Processing in its Proceedings and Report Series. Awards and Nominations The Claude E. Shannon Award The Claude E. Shannon Award 2009 was awarded to Jorma Rissanen for "consistent and profound contributions to the field of information theory." It is the highest honor of the IEEE Information Theory Society. He has previously received the 1986 Information Theory Paper Award and a 1998 IT Golden Jubilee Award for Technological Innovation, as well as the 1993 IEEE Hamming Medal. FiDiPro Award Professor Stuart Kauffman who is one of the leading reasearchers in fields of theoretical biology, complexity and systems biology was nominated Finland Distinguished Professor by TEKES. His expertise matches well the competence of the research group led by Professor Olli Yli-Harja serve each other very well. The research results are expected to enhance our understanding of gene networks dynamics including in the case of diseases, namely cancer. The results can be utilised to better understand the

21 21 RESEARCH GROUPS RESEARCH GROUPS Networked multimedia systems group Team leader: Professor Irek Defée Group activities are in the area of mobile television, home networking, client-server systems and information retrieval. EU project Pluto has been successfully completed and in result of it a full testbed for mobile television based on the DVB-H standard is operational for use in research. In projects done with industry extensions for the system information of the DVB-H standard were developed and accepted by the standardisation body. Also Tekes project UUTE2 has been completed with new concepts for home sensor networks developed and tested. The work on sensor networks was continued in the European project Feel@home and resulted in new high-lelvel architecture for advanced sensor networks based on the forthcoming Bluetooth Low Energy standard. In basic research on information retrieval one PhD in the image database retrieval based on feature histograms was completed. The work is continuing in the area of objecf contour description. Several Master of Science thesis in the area of image processing and networked multimedia were finished. The results are documented in conference and journal publications. Transforms and Spectral Methods Team Leader: Professor Karen Egiazarian Spectral and algebraic methods play a central role and mark a large and important field in modern signal processing. Broadly speaking, they comprise all types of harmonic analysis applied to signals of interest. We consider the synergy of abstract mathematical constructions, such as function space bases, frames, function decompositions and projections, with their practical implementations through fast discrete structures. The following projects are the main directions of our fundamental and applied research. LASIP project Spatially adaptive Local Approximations in Signal and Image Processing (LASIP) techniques are developed for various image processing problems: -image denoising and deblurring, - blind multiple channel image deblurring, - 3D optical sectioning, - color-filter array interpolation (demosaicing) of noisy data, - nonparametric regression estimation techniques, - shape-adaptive transforms for image denoising, deblurring, and enhancement. Non-local adaptive transform methods for image denoising and interpolation:, - 3D transforms for still-image filtering - shape-adaptive 3D transforms for still and video image denosing Signal-dependent noise analysis, modeling, and estimation: - noise model derivation for raw data from digital cameras - algorithms for non-gaussian data processing adaptive to particular features of camera s sensor - models and algorithms for clipped non- Gaussian heteroskedastic data processing 3D Visual Communications and Video Processing for Mobile Devices Dynamic 3D scenery capture, representation, coding and restoration, Optimized visualizations on auto-stereoscopic displays, Error-resilient coding of stereo video for wireless channels, Non-uniform resampling, High-Dynamic Range Imaging, Bayer pattern image compression. Digital Holography Non-uniform sampling of a diffraction field, Inverse holographic imaging, Forward and backward propagation modeling for wave field in coherent optics, High-accuracy interferometric measurements, Phase retrieval problems, Phase unwrap problems. Transforms methods for electroencephalography (EEG) Automatic removal of ocular and muscular artifacts in the EEG, Blind inversion of volume conduction effects in scalp EEG recordings, Robust indices of synchronization and causality between EEG sources Spectral Techniques and Decision Diagrams for Compact Representation of Switching Function RESULTS AND ACHIEVEMENTS IN Joint TUT/Nokia postgraduate course on Mobile Imaging The Mobile Imaging postgraduate course was organized by TUT and Nokia during periods 2 and 3 of academic year.the course provided a wide and thorough overview on mobile imaging. Series of lectures were given by the leading imaging experts from both Nokia and TUT, covering a variety of aspects related to the imaging pipeline of mobile devices.

22 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT A significant part of the course was also a project work, in which students had to implement specific mobile imaging tasks. The lectures from the TUT side focused on advanced techniques recently developed by the Transforms and Spectral Techniques Group of TUT Mobile 3DTV The Department was appointed for scientific coordination of the European project entitled Mobile 3DTV Content Delivery Optimization over DVB-H System ( It is a three-year project partly funded by the European Union 7th RTD Framework Programme and it is the first FP7 project coordinated at TUT. The project started on 1 January 2008 and is carried out by a consortium of three universities (Tampere University of Technology, Finland; Technical University of Ilmenau, Germany; Middle East Technical University, Turkey), one public research institute (Fraunhofer HHI, Germany), and two SMEs (Tamlink Ltd., Finland and MM Solutions Ltd., Bilgaria). The scientific leader is Dr. Atanas Gotchev from the TRANS group. Best paper award at EUSIPCO 2008 Alessandro Foi received the "Best Paper Award" at the EUSIPCO 2008 conference for his paper entitled "Practical Denoising of Clipped or Overexposed Noisy Images". The paper was selected by a committee of experts out of more than 1000 submissions.the paper considers the denoising of signals from clipped noisy observations, such as digital images of an under- or over-exposed scene. The results, which follow from a precise mathematical formulation of the problem, have general applicability and can be "plugged" into current filtering implementations, to enable a more accurate and better processing of clipped data.the European Signal Processing Conference EUSIPCO 2008 was held in Lausanne, Switzerland, August 25-29, An extended version of this work is published in Elsevier Signal Processing Journal Set of algorithms based on Block-Matching 3D (BM3D) concerning denoising, deblurring, demosaicing and other applications (see, are recognized as state-ofthe-art in the field. A set of open-source software tools has been developed within the project to create a full set of real-time and simulation tools for the stereovideo compression and for the application, link and physical layers of the DVB-H channel. The project developed and demonstrated the worldwide first end-to-end DVB-H based system, featuring transmission of stereo-video streams encoded by multi-view coding (MVC) and simulcast and their reception by portable devices, either equipped with 3D display or legacy ones. The system was demonstrated at the NEM Summit, held in October 2008 in Saint-Malo, France and at the ICT Event, held in November 2008 in Lyon, France. The system is constantly broadcasting stereo video over the university campus and the Hervanta suburb of Tampere. The first version of the handheld technology demonstrator is to be demonstrated at the World Mobile Congress, February 2009 in Barcelona, Spain

23 23 RESEARCH GROUPS Figure 1: Scalability in three different dimensions. Audio, Image and Video Analysis (IVA) ( Team leader: Professor Moncef Gabbouj Video Analysis, Streaming and Compression Techniques for multiview video and scalable video The Advanced Video Coding (H.264/AVC) is the state-of-art video coding standard which has been developed by the Joint Video Team of ISO/IEC MPEG and ITU-T VCEG. Multiview video has gained a wide interest recently. It has been widely developed in numerous products and services, such as TV broadcasting, video conferencing, mobile TV, and Blue-ray Disc. To support other application scenarios, for example, video delivery over homogeneous networks, enhanced user experiences in different dimensions, different video representations of a scene are desired. JVT has developed the video coding standards as the extensions of H.264/AVC. They are the scalable extension (see different modes of scalability in Fig. 1) and the multiview extension, namely Scalable Video Coding (SVC) and Multiview Video Coding (MVC) standards. In this work, SVC and MVC are considered in an end to end system. The contributions of the work include error concealment and encoder algorithms for SVC, MVC standard design (see MVC architecture in Fig. 2), error concealment and coding techniques for multiview video and 3D video contents. The encoder algorithm for SVC temporal scalability improves the coding performance for H.264/AVC with a hierarchical temporal scalable coding structure. The error concealment algorithms for SVC and MVC target frame loss cases and provide significant quality improvements for the reconstructed video sequences. A series of coding tools have been provided for MVC coding, either to improve the coding efficiency or to reduce the decoding complexity. In the context of 3D video coding, depth maps are considered. Part of this work also focuses on the coding of depth maps for 3D video, to represent the 3D video efficiently, with a lower bandwidth.

24 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT Figure 2: MVC system architecture. Video Coding with Adaptive Interpolation Filtering In order to compensate for the temporally changing effect of aliasing and improve the coding efficiency of hybrid video coders, adaptive interpolation filtering (AIF) has been recently proposed. However, the improvement in the coding efficiency from adaptive interpolation usually comes with the expense of a significantly increase in encoding and decoding complexity (upto 3 times) compared to the standard H.264/AVC codec. We proposed a novel adaptive interpolation scheme for video coding with motion compensated prediction. The developed scheme achieves a high coding gain compared to the standard H.264/AVC (up-to 25% of bit-rate reduction), whereas having comparable complexity at the decoder side. The developed scheme benefits from utilization of filters with tunable properties, such as switching filter structure and flexible filter symmetry. The encoder selects the optimal filter structure and symmetry, and signals this information to the decoder. By doing this, an efficient use of filter tap-length and overhead information is achieved. In order to reduce encoder complexity with adaptive interpolation, we developed a number of fast encoding algorithms and achieved a significant complexity reduction with negligible penalty on the coding efficiency. The most recent encoder design has about to 20-30% of complexity increase in comparison to the encoder with nonadaptive interpolation, whereas conventional AIF schemes feature 200% of complexity increase. Feedback based error resilient video coding Feedback-based error-resilient video coding relies on efficient transmission of feedback messages. Recently, an RTP profile known as the audio-visual profile with feedback (RTP/AVPF) has been often used in low-latency conversational video applications, such as video telephone. In this work, an RTP/AVPF-compliant feedback generating solution for reference picture selection (RPS) has been investigated. The proposed solution leads to more efficient use of back-channel bandwidth compared to traditional negative acknowledgment (NACK) or positive acknowledgment (ACK). Therefore high error resilient performance was achieved by effective transmission of feedback messages under the back-channel bandwidth constraint. Advances on Video Coding and Streaming Advanced algorithms for video encoding and streaming are presented in this work. The specifications of most video coding standards define only the bit-stream syntax and the decoding process. The encoding process is not standardized to permit flexible implementations. We proposed algorithms for encoding process with concentration on video rate control. The encoding process is very important such that it has a great impact on the rate-distortion performance and also on the utilization of different resources including processing power, transmission bandwidth, and delay.

25 25 RESEARCH GROUPS As a new approach, fuzzy logic controllers, Fig. 3, have been utilized in several video encoding and streaming scenarios and very good results have been provided. Video rate control algorithms for encoding variable bit rate video bit streams are proposed in which the fuzzy controllers are deployed. The proposed algorithms in the new approach are very different from the conventional rate control algorithms. However, some theoretical and practical results of conventional video rate control are used in the new approach. In comparison to the conventional methods, the new approach provides a better performance with much less lower computational complexity. Moreover, video encoding techniques optimized for streaming over DVB-H (Digital Video Coding for Handheld) are proposed in this work that according to the best knowledge there is no any similar conventional method. Figre 3: Video Rate Controller First, video rate control algorithms and tools for video streaming applications are proposed. However the proposed rate control methods in this part can be applied to some other variable bit rate video applications. Secondly, video encoding and rate control algorithms are proposed that are optimized for video streaming over DVB- H channels. Finally, video encoding algorithms are proposed for a digital video broadcast system in which a number of video sources are encoded and broadcasted simultaneously. Hybrid Modeling of DCT Coefficients for Real- Time Encoding We developed a framework to run joint experiments with different transforms, scanning methods, quantization tables and other relevant parameters. A lot of experiments were made to optimize the encoding and decoding for DCT based video compression. The experimental results were compared and evaluated with the standardized video coding. Hybrid Modeling of intra DCT Coefficients for Real-Time Video Encoding The two-dimensional discrete cosine transform (2-D DCT) and its subsequent quantization are widely used in standard video encoders. However, since most DCT coefficients become zeros after quantization, a number of redundant computations are performed. This work proposes a hybrid statistical model used to predict the zeroquantized DCT (ZQDCT) coefficients for intra transform and to achieve better real-time performance. First, each pixel block at the input of DCT is decomposed into a series of mean values and a residual block. Subsequently, a statistical model based on Gaussian distribution is used to predict the ZQDCT coefficients of the residual block. Then, a sufficient condition under which each quantized coefficient becomes zero is derived from the mean values. Finally, a hybrid model to speed up the DCT and quantization calculations is proposed. Experimental results show that the proposed model can reduce more redundant computations and achieve better realtime performance than the reference in the literature at the cost of negligible video quality degradation. Experiments also show that the proposed model significantly reduces multiplications for intra DCT and quantization. This is particularly suitable for many processors in portable devices where multiplications consume more power than additions. Computational reduction also implies longer battery lifetime and energy economy. Simplified Video Coding for Digital Mobile Devices As most mobile devices are currently suffering from the lack of computational power and energy-consumption constraints, there is significant interest and research in reducing the computational complexity for fast video coding. This work proposes a statistical model to predict the zeroquantized DCT (ZQDCT) coefficients for 3-D DCT video coding and thus to speech up the encoding process. First, each 8x8x8 pixel cube at the input of DCT is decomposed into a mean value and a residual 8x8x8 pixel cube. Subsequently, a statistical Laplacian model is mathematically developed to predict the ZQDCT coefficients. Finally, the redundant calculations for these ZQDCT coefficients are skipped. Compared to the baseline encoding method, the proposed model can significantly simplify the complexity and achieve better real-time performance. Laplacian Modeling for Real-Time Encoding Digital image/video coding standards are becoming more and more important for multimedia applications. This work proposes a Laplacian based model to reduce the complexity of the encoding process. Compared with the standard encoder and the reference in the literature, the proposed model can significantly simplify the computations

26 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT and achieve the best real-time performance at the expense of negligible visual degradation. Merged Inverse Quantization and IDCT for Optimized Decoder Implementation This work proposes an efficient technique to reduce the complexity of implementation for inverse discrete cosine transform (IDCT)-based video decoders. The proposed method merges the inverse quantization and IDCT into a single procedure, which is referred to as inverse quantized IDCT (IQIDCT), such that the decoded coefficients do not need to be inverse quantized prior to the inverse transform. Thus, the computations related to inverse quantization are omitted. Since the cosine transform basis can be constructed before decoding, the proposed IQIDCT effectively replaces the need for computing power with little additional memory. The performance of the proposed algorithm is evaluated by comparing it with the original XVID decoder which uses the traditional separate inverse quantization and IDCT method. Experiments show the efficiency of the proposed method in reducing the overall decoding complexity. Moreover, it does not result in any video quality degradation. The proposed method is particularly suitable for low-power processors in multimedia systems. Error-Resilient Communication Using the H.264/AVC Video Coding Standard The Advanced Video Coding standard (H.264/AVC) has become a widely deployed coding technique used in numerous products and services, such as Blu-ray Disc, Adobe Flash, video conferencing, and mobile television. H.264/AVC utilizes predictive coding to achieve high compression ratio. However, predictive coding also makes H.264/AVC bitstreams vulnerable to transmission errors, as prediction incurs temporal and spatial propagation of the degradations caused by transmission errors. Due to the delay constraints of real-time video communication applications, see e.g. Fig. 4, transmission errors cannot usually be tackled by reliable communication protocols. Yet, most networks are susceptible to transmission errors. Consequently, error resilience techniques are needed to combat transmission errors in real-time H.264/AVCbased video communication. The aim of the work is to improve the error robustness of H.264/AVC in real-time video communication applications. Efficient coding for future generation codecs The aim of this work is to develop and implement efficient coding algorithms that provide higher coding efficiency for the future international video coding standard beyond H.264/AVC. A novel algorithm called spatially varying transform (SVT) was proposed to improve the coding efficiency of video coders. SVT enables video coders to vary the position of the transform block, unlike stateof-art video codecs where the position of the transform block is fixed. In addition to changing the position of the transform block, the size of the transform can also be varied within the SVT framework, to better localize the prediction error so that the underlying correlations are better exploited and the coding efficiency is improved. Gains become more significant at high bit-rates for most tested sequences and the bit-rate reduction can be up to 13.50%, which makes the proposed algorithm very suitable for future video coding solutions focusing on high definition and high fidelity video applications.

27 27 RESEARCH GROUPS Figure 4. Video Compression in Internet, television broadcast networks, and mobile networks. Error resilience techniques, e.g., applicable for H.264/AVC-based real-time video communication, are commonly classified into interactive error control, forward error correction and concealment, and error concealment by postprocessing. Interactive error control methods try to avoid the emergence of transmission errors proactively or compensate the transmission errors reactively by cooperation between the transmitter and the receiver. Forward error correction and concealment refers to those techniques in which the transmitter adds redundancy to the transmitted data enabling the receiver to recover or estimate the contents of the transmitted data even if there were transmission errors. Both interactive error control and forward error correction and concealment can be applied equally to all parts of a transmitted bitstream or unequally, e.g., being biased by the impact of the respective protected part on the reconstructed video quality. Error concealment by postprocessing refers to the estimation of the correct representation of erroneously received data. We also discuss the choice of the most useful error resilience techniques, which depends on the application and network in use. We present methods to improve error resilience from the level achievable by earlier methods. The presented methods can be grouped into three topics: isolated regions (Fig. 5), subsequences and interleaved transmission, and encoder-assisted error concealment. The isolated regions technique falls into the category of forward error concealment methods and it can also be used as a tool for region-of-interest partitioning for unequal error protection. The subsequence technique provides means for hierarchical temporal adaptation of the coded bitstream. In other words, parts of the bitstream can be decoded to obtain a subsampled picture rate. It is shown that the sub-sequence technique improves compression efficiency compared to non-hierarchical temporal scalability and nonscalable bitstreams. Furthermore, two error resilience schemes utilizing the sub-sequence technique are presented: an unequal error protection scheme in which interleaved transmission is required and a forward error concealment scheme called intra picture postponement. In the final part, two encoder-assisted error concealment methods are presented. These are shown to improve the handling of transmission errors in certain situations. A part of the research work was carried out within the standardization efforts of H.264/AVC. Specifically, isolated regions, sub-sequences,and the presented encoder-assisted error concealment methods were adopted in H.264/AVC, and the interleaved transmission feature was included in the specification for real-time carriage of H.264/AVC bitstreams over the Internet Protocol. isolated region leftover region slice 0 slice 1 slice 2 slice 3 Figure 5. Example partitioning of a picture to an isolated region and a leftover region and further to slices.

28 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT Query Image Feature Extraction Features Display Results Similarity Measurement User ONLINE OFFLINE Image Features Feature Extraction Image Database Figure 6: Content-based image indexing and retrieval process. Content-based Indexing and Retrieval over Large Audio, Image and Video Databases Interactive multimedia services will strongly influence and even dominate the future of communications and telecommunications. Both the flexibility and efficiency of the coding systems used, as well as the ability to efficiently search for particular content of interest on distributed databases are essential for the success of these emerging services. Since the early 1990s, content-based retrieval of digital imagery, see Fig. 6, has become a very active area of research. In this context we have been developing the MU- VIS, which is a system for content indexing and retrieval for multimedia databases. Several topics have been investigated in this field, some of which are briefly described next. Similarity Measures of Audio for General Query by Example Application Query by example refers to finding multimedia items from a database automatically, which are similar to the example provided by the user. This is an important task in modern multimedia databases. This work deals with the automatic query by example of audio samples. The emphasis is on representation and distance measures between two audio signals, which are used to estimate the similarity of these two signals. The work also covers computational issues, which are highly important when it comes to practical implementations of the algorithms. Two different audio signal representations are proposed. These representations are interconnected, since the first separates drums from a polyphonic music signal. However, the same approach could be used to separate other parts from the original signal as well, for example, harmonic instruments. The second representation models the harmonic sound using only a few parameters. The proposed method is based on Mel frequency cepstral coefficients, which are further modeled using attack-decay-sustain-release curves using temporal evolution of harmonic instruments. Most of distance measures, used in audio signal processing, are based on dividing a signal into frames, extracting perceptually motivated features from each frame, and calculating the distance between the features. Most of the proposed distance measures use Gaussian mixture models to estimate the probability density functions of the frame-wise features and calculate the distance between the Gaussian mixture models. However, we also introduce a parameter free distance measure. This is based on compression ratios of audio signals and, hence it removes the user influence on the results, since no features or other parameters need to be set. In a query by example application, the similarity between the example provided by the user and each database item need to be calculated to achieve the best accuracy. However, in practical applications this operation is exhaustive if the database contains, for example, millions of items. The proposed method applies key-sample transformation to reduce the series of feature vectors, used to represent each signal, into a single feature vector. The database is then clustered and the search is restricted to only few clusters, thus saving retrieval time with some loss of accuracy.

29 29 RESEARCH GROUPS Description: 2D Walking Ant Histogram (2D WAH) 2D WAH is a novel shape descriptor, which can be extracted from the major object edges automatically and used for the multimedia contentbased retrieval in multimedia databases, is presented. By adopting a multi-scale approach over the edge field where the scale represents the amount of simplification, the most relevant edge segments, as we refer to sub-segments, which eventually represent the major object boundaries, are extracted from a scale-map. Similar to the process of a walking ant with a limited line of sight over the boundary of a particular object, we traverse through each sub-segment and describe a certain line of sight, whether it is a continuous In this work we propose a novel concept, ordinal co-occurrence matrix, based on combining traditional gray-level co-occurrence matrices and ordinal descriptors. We introduce a novel framework for developing ordinal co-occurrence matrix features. Three practical approaches are implemented and presented as particularizations of the framework. The framework can also accommodate other possible variations, and therefore it can be used as a basis for developing other texture feature extraction methods that are invariant to monotonic gray level changes. These feature extraction methods could then be applied to image retrieval and classification applications, for instance. In this work retrieval performance of the different ordinal co-occurrence methods are compared against other well-known methods, a retrieval example is shown in Fig. 7. Figure 7: Example of texture retrieval. The example image is in top left corner and the reseived images are in the right. The number below the image tells its distance to the example. branch or a corner, using individual 2D histograms. Furthermore, the proposed method can also be tuned to be an efficient texture descriptor, which achieves a superior performance especially for directional textures. Measures for Similarity Evaluation Applied to Texture and Shape Retrieval In many application domains, such as remote sensing and industrial applications, the image acquisition process is affected by changes in illumination conditions. In several cases only the structure of the gray level variations is of interest. Therefore, invariance to monotonic gray-level changes is an important property for texture features. In reality, illumination changes are not necessarily monotonic, but for the case of simplicity in this work we deal with only monotonic illumination changes. We also proposed a novel ordinal approach for shape similarity estimation. The proposed method operates in three steps: object alignment, contour to multilevel image transformation, and similarity evaluation using ordinal correlation framework. The retrieval performance of the method is evaluated using the MPEG-7 shape test database and the method is also applied to objective performance evaluation of segmentation algorithms. The proposed technique produces encouraging results in both experiments. Perceptual Color Descriptors The research work on perceptual colour descriptors has been extended to emphasize human visual perception. The aim is to apply such perceptual techniques to 3D objects in order to extract accurate shape descriptions for 3D object retrieval.

30 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT Selection Advances on Content-Based image Indexing and Retrieval Performance Various methods, algorithms and systems have been proposed addressing multimedia storage and management problems. Such studies reveal the indexing and retrieval concepts, which have further evolved to Content-Based Image Indexing and Retrieval (CBIR). CBIR systems often analyze multimedia content via the so-called lowlevel features for indexing and retrieval, such as color, texture and shape. In order to achieve significantly higher semantic performance, recent systems seek to combine low-level with highlevel features that contain perceptual information for humans. However, such combinations increase the feature extraction processing time and the memory requirements as well as the retrieval complexity. Performance optimization of indexing and retrieval plays an important role for providing advanced CBIR services on any hardware platform. In this work, we propose novel techniques for improving the overall performance of CBIR. We define general CBIR challenges as memory and disk space requirements, computational complexity, semantic retrieval performance and usability complexity. Significant contribution of this work is to bring elaborate and feasible solutions to the challenges. A novel system for feature selection is introduced for enhancing semantic image retrieval results, decreasing retrieval process complexity, and improving the overall system usability for endusers of multimedia search engines. Three feature selection criteria and a decision method construct the feature selection system. A majority voting based method is adapted for efficient selection of features and feature combinations. The performance of the proposed criteria is assessed over a large image database and a number of features, and compared against other techniques from the literature. Experiments show that the proposed feature selection system improves semantic performance results in image retrieval systems. We introduced a novel Transform-Based Layered Query (TLQ) scheme, see Fig. 8, designed for efficient handling of visual media retrieval, which mainly aims at decreasing processing time and run-time memory consumption without degrading retrieval results semantically. The scheme is based on abstract layers in indexing and retrieval phases where each indexing layer of TLQ corresponds to a retrieval layer. The layers are independent from the underlying indexing and retrieval methods, and mainly constructed using multimedia and feature data transformations for reducing data dimensions. A twolayer TLQ system is implemented and integrated into the MUVIS content-based multimedia indexing and retrieval framework. A new feature dimension reduction method referred to as Mapping by Adaptive Threshold (MAT) is also proposed as a solution for memory requirements and the computation complexity of the retrieval process. The theoretical and practical advantages of the TLQ over existing methods are verified experimentally on image databases using the MAT method for feature data. Experimental studies also show that the proposed MAT method is a fast feature transformation for successfully reducing the dimension of feature data without degrading semantic retrieval performance significantly.we also studied the effects of image downscaling techniques on semantic retrieval performance via dedicated experiments in order to utilize the downscaling methods in the TLQ scheme. Several images are collected from various sources and experimental databases are generated by applying image compression and downscaling. The evaluation results show that image downscaling does not have significant impact on color and texturebased retrieval in general, while it degrades edge-based retrieval performance significantly. T1 Feature Extraction Original Feature Vector T2 Transformed Feature Vector Figure 8: Overview of the transformation scheme In order to accomplish the primary objective of the work, a novel study on system profiles and adaptation of parameters for end-users of a CBIR system are presented. The main aim of the study is to optimize the overall CBIR system performance in different hardware platforms having different technical capabilities and conditions.

31 31 RESEARCH GROUPS We define CBIR system profiles in terms of hardware and system platform properties and propose personalized CBIR parameters for each defined system profile. The performances of the proposed parameters for each system profile are assessed over a large set of experiments. Experimental studies show that the proposed parameters for each system profile improve semantic performance, while reducing computational complexity and storage requirements. PSO-Based Dominant Color Extraction Dominant color extraction via dynamic color clustering using M-D PSO has been the major research subject. The extension of this work will focus on texture clustering/segmentation using Gabor features within M-D PSO and later integrating the color descriptors. As part of his training at Kodak, Stefan Uhlman has investigated face recognition (FR) approaches. This led to an evaluation of some freely available and self-implemented face recognition algorithms over common FR datasets and some consumer photo collections. Voice Conversion and Speech Synthesis, Data Alignment in GMM based Voice Conversion The goal of voice conversion is to transform speech from a source speaker to sound as if it was spoken by a target speaker while maintaining the lexical content of speech. The idea is to cope with only a few training sentences which is challenging. Parametric techniques, such as Gaussian mixture models (GMMs), are used widely in this context due to their robustness. In many cases it is assumed that we have parallel data from the source and the target which have to be properly aligned for the training. Thus the accuracy of the alignment plays an important role in the final conversion quality. Examples of alignment techniques include the usage of a speech recognizer with forced alignment or dynamic time warping (DTW). According to our experiments, alignment clearly matters but with simple DTW and some constraints we can achieve the same quality as with hand-marked labels. Since DTW leads to a globally optimal solution, it is beneficial to remove inappropriate data which are frame pairs containing clearly non-matching data as well as silence-silence pairs. GMM Based Voice Conversion The previous work on voice conversion in narrowband continued first with a study of the synthetic-to-human voice conversion, a practical case found in real applications. An experiment of cascaded voice conversion followed. The research shifted to a wideband framework after the integration of the new wideband codec. The spectral warping is a new technique offering improved sound quality yet having its own problems like getting a data driven warping function or set of warping functions reliably and mapping formant amplitudes. A study employing PCA was aimed at getting reliable warping functions. The spectral metrics and their role in getting a perceptually relevant clustering were the subject of another study trying to answer questions like how the metrics relate to each other and what is an optimal number of clusters. A major issue in GMM voice conversion is the robustness when estimating covariance matrices (of GMM mixtures) especially in situations where the training data is limited. Some experiments investigated this aspect and checked the meaningfulness of using decorrelated features (by DCT). The use of perceptual distances on LSFs and the use of perceptual weighting in model estimation were also studied as a separate issue. Further studies on LSF tried to answer questions like what is a perceptually meaningful average LSF and how time resolution in LSF feature affects the speech quality. The research on frequency warping was complemented with the study of a cascaded combination of frequency waping and GMM and with the implementation of several pitch mapping schemes based on frequency warping. An efficient model reestimation scheme based on an existing welltrained conversion model for a new target speaker with only a very small amount of training data was proposed. Finally some work was devoted to learning about the Hideen Malkov Model (HMM) based Text to speech TTS (HTS) which is catching up lately with the quality of concatenative TTS and offers new possibilities and challenges for voice conversion from a different perspective (currently MLLR linear regression adaptation is used). Corpus-based speech synthesis methods Previously, a unit selection text-to-speech (TTS) system for Finnish has been developed at TUT. The system consists of a speech database containing of 1.5 hours of recorded speech, a text processing part that parses the orthographic input text into a phonetic form, and a waveform generation part that selects the suitable speech units from the database and concatenates them in order to form the output speech waveform. During 2008, TTS research has extended to cover hidden Markov model (HMM) based TTS as well. In this research, the existing Finnish text processing module has been utilized with the required modifications. As HMMs are a parametric technique, they are first trained based on the speech parameters extracted from the speech database and the synthesized speech is then generated based on the parameters of the

32 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT trained models. In general, the overall quality of the synthesized speech is more stable than in unit selection. Since the averaging models are used in synthesis instead of the actual speech segments, the number of inconsistencies is smaller than in unit selection. In our subjective evaluations, the new HMM-based TTS system was also found to provide better prosody (in terms of intonation) compared to unit selection system using the same speech database. and length of a supersonic bullet using a microphone array. The self-localization of microphones was investigated. The group produced a number of journal and conference papers. Web-pages ofthe group can be found at Audio Research Group Team leader: Professor Anssi Klapuri Audio Research Group consists of 17 people who do research on audio signal processing. Most of the group members (9 of them) are Ph.D. students, funded either from graduate schools or from projects. Traditionally, industrial funding sources have been quite important in audio research and several new projects started in 2008 and 2009, too. Audio Research Group is organized into three teams that work on speech signals, music signals, and spatial audio, respectively. In speech processing, prominent research topics in 2008 and 2009 included voice conversion, text-to-speech synthesis for Finnish, speech separation, and noise robust automatic speech recognition. In the music processing team, research was carried out on music transcription, sound separation, music structure analysis, query-by-example of audio, sound source recognition, automatic transcription of singing, automatic transcription of drums, and time-strecthing of audio. The group started more intensive research collaboration with Helsinki University of Technology on speech and singing recognition and several research visits took place between the two institutions. The spatial audio team worked for example on the localization of impulsive sounds sources and speaker localization in a room, and developed a real-time camera control algorithm that is directed towards the speaker. A track before detect (TBD) approach for tracking multiple speakers was published using sequential Monte Carlo methods (particle filters). The method is able to track speaker locations and detect voice activity of multiple overlapping speakers in a room environment using a distributed ad hoc microphone array. The TBD paradigm enables tracking of weak sources in noisy environments. The detection was based on a likelihood ratio, where the likelihoods are estimated from particle weights. A method for the estimation of supersonic bullet trajectory using Monte Carlo methods was investigated. The system is capable of determining the bullet trajectory, speed, caliber

33 33 RESEARCH GROUPS NAMU Lab. Team leader: Adj.-Prof. Dr. Artur Lugmayr Media evolved from media that can be described as integrated presentation in one form (multimedia), towards embedding the consumer into a computer graphic generated synthetic world (virtual reality), to the consumers' directly exposed to the media in their natural environment, rather than to computer interfaces (ambient intelligence), and will be evolving towards a fully real/synthetic world indistinguishable pure media (biomedia or biomultimedia). NAMU provides a very special environment for the exploration of ideas by interconnecting disciplines and leaving creative scientific 'madness' a place. NAMU means in Finnish 'candy' or 'sweets', excellently fitting to the objective to the group, to scientifically explore the tomorrow of media technology and its related services. The group's motivation is "being innovative, creative and looking beyond pure technologically focused thinking - there is more than just coding software out there. There are people needed to turn technology into a consumer experience." NAMU was founded in 2003 by Artur Lugmayr at the Digital Media Institute (DMI) with the intention to give a new viewpoint towards media technology by using ambient intelligence. Currently NAMU focuses on visionary and future envisioning approach towards the development of new forms of entertainment experiences. In 2008 the group generated 5 MSc. thesis; supervised 7 internships and practical trainings; attracted students to 5 given courses (Ambient Multimedia Seminar, Methods of Digital Media Production, Virtual Reality Seminar, Virtual Reality, and Broadcast Multimedia); completed the ENTHRONE 2 IST EU project in the topic of metadata management for QoS; established an open source software forum (Portable Personality P2); was involved as general chair or in other higher level duties in the organization of 6 conferences/workshops (e.g. EuroITV, Academic MindTrek, uxtv); held over 5 keynotes and talks at high level conferences; was involved in the establishment of a interactive digitaltv laboratory in Buenos Aires/Argentina; and published more than 20 scientific publications as editors, authors, journals, or book chapters. The group is embedded in many initiatives: the Centre of Excellence of Signal Processing (SPAG), ISO/IEC MPEG standardization, Swan-Lake Moving Image & Music Award, etc.

34 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT

35 35 RESEARCH GROUPS A Pseudo-Volumetric, Immaterial 3D Display Team leader: Dr Ismo Rakkolainen Dr. Ismo Rakkolainen is working for the Academy of Finland s postdoctoral researcher s project. The research is based on immaterial projection screen technology, an entirely new kind of a display, for which he is a co-inventor. The 2D walk-through FogScreen has received enormous amounts of international media attention and has intrigued audiences in demonstrations around the world. It has won several innovation awards, e.g., EU s distinguished 2005 European IST Prize. The main objective of the project is to explore and develop an immaterial pseudo-3d display and new kinds of multimodal and perceptual user interfaces for it. The research combines humancomputer interaction, 3D graphics, virtual and augmented reality, tracking and display technologies. This project will explore new kinds of longer-term technologies to discover and exploit the immaterial display technology s full potential. The enhanced 3D FogScreen will have robust, unencumbered head tracking for head parallax and hand tracking for interaction. The setup can be stereoscopic and two-sided screen. It then becomes a fully walk-through and walk-around pseudo-3d display and will look a little like what the general public or media often describes as holographic display. The results in include proof-of-concept prototypes, 1 journal article, 2 accepted book Chapters, 4 published and 1 submitted conference papers, 1 published and 1 submitted workshop papers, 1 poster and 1 PCT patent application. The results may significantly contribute to general display and user interface technologies. The project involves close joint research with the University of California at Santa Barbara, USA, where Dr. Rakkolainen has been a visiting researcher in TUT and FogScreen Inc. from Finland were also partners in EU s Network of Excellence 3DTV project, which ended in August M 2 obsi group Team leader: Professor Ulla Ruotsalainen Tomography imaging is a very important way to have information from objects without breaking them. The M 2 obsi group aims to develop signal processing tools to analysis the structure e.g. shape of the biological objects, make the image reconstruction from measured projections and define the functions from the dynamic tomography time-sequence image or measurement sets. The goal is to improve the quantification of these measures by automation of the analysis and improving the quality of the measured signals. We have been active in developing the positron emission tomography (PET) image reconstruction and analysis. Examples of the achievements of the group are new correction methods for missing data in PET projections (Tuna et. al. IEEE TMI 2009, in press). These will be distributed for all ECAT HRRT PET users via the next release of the scanner software. Also a new method to extract directly from measured PET projections the time-activity-curves needed for physiological modeling of PET data was developed (Krestyannikov et. al Phys Med Biol). Recently the group has started to work with dynamic fluorescent microscopy imaging, as well as, with functional magnetic resonance images (MRI). Especially the group has succeeded in reducing fmri noise via ICA and supervised classification (Tohka et. al. NeuroImage 2008). The method has already gained many applications one of these studies was published in Science. The group has also developed new software for the analysis of large set of individual fmri studies recorded during film watching. Improvements in the analysis of the images open new possibilities in medical and biological research. The greatest impact of this research will, however, have in the development of new drugs. Quantitative analysis of receptor occupancy change during a drug treatment is an example of applications which can be made more automatically with the developed methods of our group (Wallius et. al. Nucl Med Com 2008). We have collaborated with pharmaceutical companies and institutions serving these companies in the research. Later on, these methods may also come to use in clinical hospital environment.

36 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT The upper image shows the activation in brain without noise correction and in the lower case the noise has been corrected with the developed method. Similarity maps across subjects during the 14-min drama movie (Crash, 2004) session (p < 0.005, corrected). Visual and auditory cortices show similarity across all the frequency bands, but similarity in frontal cortex, brain stem and cerebellum seems to be unique for very low frequencies (< 0.02 Hz).

37 37 RESEARCH GROUPS Digital Filters and Filter Banks Team Team leader: Professor Tapio Saramäki Good final filter and filter bank products, usually implemented using either VLSI circuits or signal processors, require both developing efficient implementation structures and generating optimization tools for the system-level design of the algorithms, which should properly take into account, in addition to the implementation form, the admissible relaxations for the traditionally stated far too stringent requirements, without investigating the application at all. A very typical example is the design of nearly perfect-reconstruction multi-rate filter banks, for which the overall system can be made substantially simpler when the errors allowed by the application are properly integrated in the optimization process. The application areas of filters and filter banks include, among others, multimedia, communications, global positioning systems, analog-to-digital and digital-to-analog converters based on sigma delta modulators, audio and speech, instrumentation, image processing, biomedical engineering, antenna arrays, switched capacity circuits etc. From the implementation point of view, VLSI circuits that have a small silicon area and power consumption as well as a high maximal sampling rate can be generated by avoiding the use of the general costly multiplier element as much as possible. For this purpose, it is beneficial to, first generate structures that require significantly fewer multipliers than the traditional ones and, then, to optimize all the coefficient values or most of them to become multiplication-free, that is, the corresponding value has a few power-of-two representation so that it can be implemented using hardwired logic. In the extreme case, no multiplication element is needed when quantizing all the coefficient values to be few powers of two. For signal processor implementations having as high overall throughput as possible, it is essential to take care of the following facts when optimizing filters and filter banks. First, these algorithms should be implemented using structures requiring very few multipliers. Second, the number of available bits in the processor should be enough for both meeting the given criteria and for keeping all the remaining finite word length effects, such as the output noise due to the multiplication round-off errors and limit cycles and parasitic oscillations, within the tolerable limits. The overall research performed by our team is roughly divided into the following subtopics. In each sub-topic, the previous work has been mentioned, due to the expected continuations, and the work done in 2008 is highlighted along with the possible continuation for the coming years. Basic Research on Recursive Digital Filters Numerous low-sensitivity and low-noise recursive filter structures, some of which are directly synthesized in the z-plane, instead of mapping an analog reference filter to this plane, and optimization tools for their design have been proposed and investigated by our team. In addition, novel systematic approaches have been generated for optimally designing multiplicationfree recursive digital filters, which are implemented either as a parallel connection of two allpass filters (lattice wave digital filters) (for both the conventional case and for case where phase linearity is of great importance) or as a cascade of these filters. In the future, similar quantization schemes will be applied to other low-sensitivity and low-noise recursive filter structures.

38 Amplitude DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT S 1 S 2 S Frequency [khz] From the theoretical point of view, structurally symmetric ladder filter structures, which include as special cases properly modified lossless discrete integrator (LDI) and wave digital ladder filter structures, provide substantially improved low-sensitivity and low-noise properties over their traditional counterparts. Some results have already been achieved, but this challenging and important research topic, from the general filter synthesis point of view, is planned to be completed together with Prof. Lars Wanhammar, Linköping University, Sweden, and his team. The re-study of various earlier constructed Remez-type algorithms, which partially rely on the original Parks-McClellan algorithm, for the design of arbitrary-magnitude recursive filters with the same or different denominator and numerator orders and for the design of recursive filters composed of all-pass sections started in This was due to the substantial improvement provided by our team to modify the original Parks-McClellan algorithm such that the resulting version exactly follows the basic principle of the Remez multiple exchange algorithm, as stated according to the approximation theory. Hopefully, the use of modified Parks-McClellan algorithm avoids all the difficulties faced when using the presently existing Remez-type algorithms. This topic is right now under investigation. The simultaneous optimization of the magnitude and phase responses of recursive filters continued. Generalizations of classical recursive digital filters such that, first, the low-sensitivity and lownoise recursive filter structures originally developed for the classical recursive filters can also be used for the generalized filters and, secondly, there exists an extremely fast Remez-type algorithm for the synthesis of both the classical filters and their generalizations. This research study started in Basic Research on Linear-Phase FIR Digital Filters Dozens of computationally-efficient linear-phase FIR filter structures, which exploit a relatively strong correlation between the neighboring impulse-response samples, and optimization tools for their design have been studied. Quantization schemes have been proposed for some of these structures for making them multiplication-free. Due to a thorough knowledge on the best existing computationally-efficient linear-phase FIR filter structure candidates, a comprehensive overview on them is well in preparation.

39 39 RESEARCH GROUPS In 2008, the work for generating various novel structures, for which the overall impulse response is first split into subintervals such that in each subinterval this response follows either a polynomial or a polynomial shaped by a proper sinusoidal function and, secondly, the resulting overall impulse response is generated by means of a proper use of accumulators, has been continued. Improved approaches for the synthesis of computationally-efficient FIR filters with an adjustable fractional delay based on the modified Farrow structure proposed by Vesma and Saramäki. In 2008, a novel structure, which outperforms all the existing ones, was proposed together with an efficient optimization tool for determining the coefficients in this structure. In 2008, our team made definitely the final effort of once more developing an efficient algorithm for the optimization of FIR filters synthesized using single-stage and multistage frequencyresponse masking approaches with the ultimate goal of arriving at the best filter designs, in terms of the arithmetic complexity. In 2008, substantial improvements in the wellknown Parks-McClellan algorithm were proposed in the translation from its original FORTRAN code to its MATLAB counterpart and in forcing it to follow exactly the basic principle of the Remez multiple exchange algorithm, according to the approximation theory. Some effects of this work were reported in Subtopic 1. Basic Research on Sampling Rate Conversion Systems Dozens of new structures for efficiently performing decimation and interpolation by an integer factor and optimization tools for their design were developed. Efficient methods on how to efficiently design and implement polynomial-based interpolation filters for many telecommunications and signal processing applications were studied. These interpolation filters can be used for performing the sampling rate conversion by an arbitrary factor efficiently. The key problem in implementing decimators and interpolators when using the so-called polyphase structures is that in conventional implementations when using linear-phase FIR filters, it is not so straightforward to exploit the coefficient symmetry of these filters. Our team has been very active together with Prof. Y C Lim and Dr. Y. J. Yu, Nanyang Technological University, Singapore, in modifying the conventional polyphase structures such that the existing coefficient symmetry is kept alive as much as possible in cases where the sampling rate conversion rate is an integer or as a ratio of two integers. Multiplication-free polyphase structures for implementing interpolation and decimation filters were studied by utilizing the coefficient symmetry, the number of required adders in the proposed structures is reduced as compared with other currently existing structures. Structures for implementing sampling rate convertors by a rational sampling rate factor utilizing the coefficient symmetry were developed. Basic Research on Filter Banks This research area is definitely the most worldwide recognized one by our team during the past decade. As a result of our team effort, a handbook chapter was published, which gives a comprehensive overview on various structures and design techniques for various multirate filter banks and transmultiplexers. These multirate systems include the most existing FIR and IIR two-channel filter banks, tree-structured and octave banks based on the use two-channel filter banks, perfect-reconstruction and nearly perfectreconstruction cosine-modulated and modified DFT M-channel filter banks, and discrete-time wavelet banks. The above-mentioned handbook chapter is partially based on many of our discoveries published as journal and conference articles. An efficient technique, based on the use of second-order cone programming, for the design of conventional and low-delay perfectreconstruction cosine-modulated filter banks together with Prof. W.-S. Lu, University of Victoria, Canada. Several methods for the design of M-channel oversampled filter banks were investigated. Although, the emphasis has been put on modulated filter banks, some non-modulated cases have also been considered. Techniques for the design of nonuniform twochannel and M-channel filter banks used in audio applications were studied. Efficient windowing-based methods for the design of modulated filter banks for use in communication applications were developed. These techniques have been developed together with P. Martin-Martin, F. Cruz-Roldán, M. Blanco- Velesco, and A. Martin-Marcos, University of Alcala, Madrid, Spain. Extensive studies of various approaches for the design of two-channel filter banks with rational sampling rate factors by utilizing the frequency-

40 DEPARTMENT OF SIGNAL PROCESSING ANNUAL REPORT response masking technique for building the filter bank filters have been performed. A method to design two-channel filter banks with rational sampling rate factors by using IIR filters was developed. Structure for implementing nearly perfectreconstruction cosine modulated filter banks with a reduced number of required multipliers by utilizing the coefficient symmetry of the prototype filter was designed. Optimization Tools for Digital Filter and Filter Bank Design Various efficient algorithms have been developed for the design of digital filters and filter banks subject to the constraints stated by the application at hand and the implementation in use (usually a VLSI circuit or a signal processor). Among these algorithms, the following two-step procedure has turned out to be the most efficient in order to guarantee the convergence at least at a good local optimum. First, a good suboptimal start-up solution is found in a systematic manner. Then, this solution is improved by means of an efficient nonlinear optimization algorithm. Using a good start-up solution for further optimization is very beneficial as it is pretty close to the optimum one. When optimizing filters and filter banks subject to the given constraints as well as when quantizing filter and filter banks coefficient values to have few powers-of-two representations, the abovementioned two-step synthesis technique has been a very efficient tool. Therefore, it will be used as a good candidate technique also in the future projects. Information Theoretic Methods for Signal Compression and Genomic Signal Processing Team leader: Professor Ioan Tabus Research area: One first research area is applying information theoretic methods in statistical modeling and inference; we propose and apply normalized maximum likelihood models for nonlinear models and inference using Kolmogorov structure function with application to studies in bioinformatics and analyzing genomic and proteomics sequence data. A second large area of research is source coding, in which we developed a number of best performing lossless audio compression methods; we proposed new optimal tree models for small files; the best performing biological sequence compression; and developed new techniques for randomly accessible data compression. Knowledge Mining Team Team leader: Professor Ari Visa There are huge amounts of data, signals, images, documents, multimedia documents. There is a need to manage the information somehow, but the pieces of information are often vague or partly missing. The research problem is "How to detect the weak signals from the available data? The most common words describing our research are knowledge mining, data mining, knowledge management and information retrieval. In other words we are extracting pieces of information from signals and from complicated multimedia documents. Several big projects have been completed and reported during the biennium. One of the projects is demonstrated here by the picture where a remote controlled helicopter is measured with a radar. Sleep and Sensory Signal Analysis Group Team leader: Adjunct Professor Alpo Värri The mission of the Sleep and Sensory Signal Analysis Group (SSSAG) is to promote health and well-being by designing analysis algorithms for signals measured from humans in various ways. The group has a long experience about analyzing physiological signals recorded in sleep laboratories such as EEG, EOG, EMG, ECG, SpO2 etc. and most recently the group has analyzed signals measuring the ballistocardiogram (BCG) and the presence of a person with sensitive movement sensors. A calibration device for the accurate force calibration of the BCG chair developed in the group was being developed. This work still continues in Additional information can be obtained from The group started a project called InterBrain together with the psychology departments of Jyväskylä and Tampere Universities in fall 2009.

41 41 RESEARCH GROUPS InterBrain is financed by the university alliance program of the universities in Tampere and Jyväskylä. The purpose of the project is to study the consequences and benefits of various interventions of people suffering from developmental and mood disorders or other brain-related handicaps. This is accomplished with the help of analyzing the EEG activity of the subjects before and after the intervention with advance signal processing methods. In addition to local studies the group participated in European research activities in the BIOPATTERN project which ended in The Grand Vision of BIOPATTERN was to develop a pan-european, coherent and intelligent analysis of a citizen's bioprofile; to make the analysis of this bioprofile remotely accessible to patients and clinicians; and to exploit bioprofile to combat major diseases such as cancer and brain diseases. SSSAG was most active in the analysis of brain diseases in this project. More information can be obtained from the web site Thanks to the long experience of participation in the work in medical device communication standardisation in Europe and within ISO, Alpo Värri was nominated to the convener of the Working Group IV, Technology for Interoperability of the Technical Committee Health Informatics (TC251) of the European Committee of Standardisation (CEN). This chairmanship lasts for three years starting September The scope of WGIV covers medical devices in hospitals including also imaging devices and devices in home care, including the rapidly growing area of personal health devices. The focus is on the information technology and communication aspects of the devices. The electrical safety issues of the devices are out of the scope. In addition to these international duties, Alpo Värri has also been the national representative of Finland in the medical device communication standardization activities. More details about European health IT standardisation can be found in Union. The aim of the project is to develop ship engines made in Europe to comply with the very tight emission regulations which will be enforced by the EU from the year 2016 onwards. One element in this emission reduction process is to monitor the state of the engine with various sensors, to analyze the sensory signals with intelligent methods and to control the engine back to the optimum performance and emission level as soon as possible in case an abnormality has been detected. The role of the SSSAG was to analyze measurements from test engines and to design the signal processing algorithms for their real time application in the engine control unit. More information can be obtained from the web site Figure 1. Researcher Pertti Suominen beside the world's oldest Diesel engine in MAN Museum, Augsburg, Germany. Sensory signal analysis was extended to a new area in The group participated in the project Higher efficiency engine with ultra-low emissions for ships (Hercules-β) financed by the 7th Framework Program of the European