CSE168 Computer Graphics II, Rendering. Spring 2006 Matthias Zwicker


 Leona O’Connor’
 1 years ago
 Views:
Transcription
1 CSE168 Computer Graphics II, Rendering Spring 2006 Matthias Zwicker
2 Last time Sampling and aliasing
3 Aliasing Moire patterns
4 Aliasing Sufficiently sampled Insufficiently sampled [R. Cook ]
5 Fourier analysis Periodic signals can be expressed as a summation of sinusoidal waves The Fourier transform computes the complex amplitude at each frequency Spatial domain Frequency domain, power spectrum
6 Convolution Spatial domain Convolution Frequency domain Multiplication
7 Sampling Spatial domain: multiply signal with impulse train Frequency domain: convolve signal with Fourier transform of impulse train Spatial domain
8 Sampling Theorem (Shannon 1949) A signal can be reconstructed exactly if it is sampled, at least, at twice its maximum frequency The minimum sampling frequency is called the Nyquist frequency
9 Antialiasing in graphics Image signals are not bandlimited to half the pixel frequency in general Prefiltering Supersampling Bandlimit Sample Sample Reconstruct
10 Supersampling Sampling patterns Reconstruction filters
11 Poisson Disk Sampling [Hanrahan] Spatial domain [Hanrahan] Frequency domain Random sampling with minimum distance constraint Dart throwing algorithm
12 Poisson Disk Sampling 2x2 Poisson sampling 2x2 uniform sampling [Dippe 85] [Dippe 85]
13 Today Reconstruction filtering Realistic camera models High dynamic range imaging
14 Reconstruction Reconstruction filters are weighting functions to compute a weighted average of the samples Continuous pixel Sampled pixel Sample Reconstruct
15 Box Filter Pretending pixels are little squares Take the average of samples in each pixel spatial frequency
16 Box filter Pixels are not little squares Original highresolution image Horizontal banding artifacts Downsampled with a 5x5 box filter (uniform weights)
17 The Ideal Reconstruction Filter Unfortunately it has infinite spatial extent Every sample contributes to every interpolated point Expensive/impossible to compute Ringing (Gibbs phenomenon) Sampled signal frequency Ideal reconstruction filter spatial frequency
18 Problems with Reconstruction Filters Excessive passband attenuation results in blurry images Excessive highfrequency leakage can accentuate the sampling grid Filters with a small support in the spatial domain have a large support in the frequency domain frequency
19 MitchellNetravali Filters [1988]
20 Reconstruction from nonuniform samples Requires normalization Samples Reconstruction kernel Nonuniform positions Pixel boundary
21 Questions?
22 Realistic camera models So far: ray tracing using the pinhole model
23 Pinhole cameras
24 Pinhole cameras Problems
25 Pinhole cameras Problems Small pinhole gathers little light, requires long exposure Larger pinhole reduces sharpness
26 Lenses Gather more light Need to be focused Lens
27 Lenses Pinhole Lens 6 sec. exposure 0.01 sec exposure
28 Thin lens model Approximative model for wellbehaved lenses All parallel rays converge at focal length Rays through the center are not deflected
29 Thin lens model How are arbitrary rays deflected when passing through a thin lens?
30 Thin lens model
31 Thin lens model Similar triangles
32 Thin lens model More similar triangles
33 Thin lens model Thin lens formula All rays passing through a single point on a plane at distance in front of the lens will pass through a single point at distance behind the lens
34 Thin lens model Focus at infinity: Film plane Closest focusing distance: Object
35 Thin lens model Out of focus film plane results in spherical blur Out of focus film planes Spherical blur
36 Depth of field Blurriness of out of focus objects depends on aperture size Aperture
37 Depth of field
38 Ray tracing using a thin lens model Place image plane at distance D from lens plane Generate primary rays with random origin on lens aperture Pinhole Thin lens Object in focus Primary rays Image plane Primary rays Image plane
39 Camera parameters Typical SLR lens Focal length 35mm fnumber f3.5 Aperture is (focal length)/(fnumber), i.e. 10mm Depth of field effects only for very short distances distances, < 5m
40 Camera parameters Typical SLR lens Field of view depends on focusing distance Film size is 36mm x 24mm Focus at infinity, vertical field of view is
41 More realistic camera models A realistic camera model for computer graphics, Kolb, Mitchell, Hanrahan Lens distortion Exposure, motion blur [Kolb et al.] Full simulation Thick lens approximation Thin lens approximation
42 Questions?
43 HDR and tone mapping HDR: high dynamic range Dynamic range: ratio of largest over smallest intensity value in image The dynamic range of light in real environments is often larger than the range of the sensor The dynamic range of rendered images is often larger than the range of the display
44 HDR photography Acquire several images with different exposures Recover a HDR intensity for each pixel [Wikipedia]
45 HDR photography Steve Mann /index.html Paul Debevec Mitsunaga, Nayar, Grossberg ects/rad_cal/rad_cal.php
46 Tone mapping Compress dynamic range of image without losing detail [Wikipedia]
47 Tone mapping Naïve approach: map fix luminance value to white using linear scaling
48 Tone mapping Contrast preserving, nonlinear scaling A contrast based scale factor for luminance display, Ward, 1994
49 Tone mapping Spatially varying nonlinear scaling A tone mapping algorithm for high contrast images, Ahiskmin, 2002
50 Multiscale methods Reduce contrast of lowfrequencies Keep high frequencies
51 Multiscale methods Halos
52 Edgepreserving filtering Do not blur across edges Nonlinear filtering (not a convolution)
53 Bilateral filter Tomasi and Manduchi 1998
54 Tone mapping with the bilateral filter
55 Tone mapping with the bilateral filter Fast Bilateral Filtering for the Display of HighDynamicRange Images, Durand et al., 2002
56 Next time Participating media and subsurface scattering
Lecture 12: Cameras and Geometry. CAP 5415 Fall 2010
Lecture 12: Cameras and Geometry CAP 5415 Fall 2010 The midterm What does the response of a derivative filter tell me about whether there is an edge or not? Things aren't working Did you look at the filters?
More informationAliasing, Image Sampling and Reconstruction
Aliasing, Image Sampling and Reconstruction Recall: a pixel is a point It is NOT a box, disc or teeny wee light It has no dimension It occupies no area It can have a coordinate More than a point, it is
More informationEECS 556 Image Processing W 09. Interpolation. Interpolation techniques B splines
EECS 556 Image Processing W 09 Interpolation Interpolation techniques B splines What is image processing? Image processing is the application of 2D signal processing methods to images Image representation
More informationSpecular reflection. Dielectrics and Distribution in Ray Tracing. Snell s Law. Ray tracing dielectrics
Specular reflection Dielectrics and Distribution in Ray Tracing CS 465 Lecture 22 Smooth surfaces of pure materials have ideal specular reflection (said this before) Metals (conductors) and dielectrics
More informationView Camera Movements and Techniques
View Camera Movements and Techniques View Camera Movements A view camera s movements, front and rear standards, provide for the ability to change and control an image, including image placement, planes
More informationUnderstanding Camera Settings
Understanding Camera Settings Aperture (Fstop) Shutter Speed ISO Exposure Triangle White Balance ISO ISO is the acronym for International Standards Organization When changing your ISO setting, you re
More informationFourier Transform and Image Filtering. CS/BIOEN 6640 Lecture Marcel Prastawa Fall 2010
Fourier Transform and Image Filtering CS/BIOEN 6640 Lecture Marcel Prastawa Fall 2010 The Fourier Transform Fourier Transform Forward, mapping to frequency domain: Backward, inverse mapping to time domain:
More informationINFOGR Computer Graphics. J. Bikker  AprilJuly 2016  Lecture 12: Postprocessing. Welcome!
INFOGR Computer Graphics J. Bikker  AprilJuly 2016  Lecture 12: Postprocessing Welcome! Today s Agenda: The Postprocessing Pipeline Vignetting, Chromatic Aberration Film Grain HDR effects Color Grading
More informationLinear Filtering Part II
Linear Filtering Part II Selim Aksoy Department of Computer Engineering Bilkent University saksoy@cs.bilkent.edu.tr Fourier theory Jean Baptiste Joseph Fourier had a crazy idea: Any periodic function can
More informationThe Interpretation of Optical Data Sheets. Carl Zeiss AG, Udo Schellenbach, PHV
The Interpretation of Optical Data Sheets Some Facts about Zeiss Since 1896 famous for Camera Lenses Mr. Carl Zeiss founded Zeiss 1846 and started collaboration with Prof. Ernst Abbe 1866 Worldwide 48
More informationNyquist Sampling Theorem. By: Arnold Evia
Nyquist Sampling Theorem By: Arnold Evia Table of Contents What is the Nyquist Sampling Theorem? Bandwidth Sampling Impulse Response Train Fourier Transform of Impulse Response Train Sampling in the Fourier
More informationOptical Metrology. Third Edition. Kjell J. Gasvik Spectra Vision AS, Trondheim, Norway JOHN WILEY & SONS, LTD
2008 AGIInformation Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. Optical Metrology Third Edition Kjell J. Gasvik Spectra Vision AS,
More informationINTRODUCTION TO RENDERING TECHNIQUES
INTRODUCTION TO RENDERING TECHNIQUES 22 Mar. 212 Yanir Kleiman What is 3D Graphics? Why 3D? Draw one frame at a time Model only once X 24 frames per second Color / texture only once 15, frames for a feature
More informationImage Processing with. ImageJ. Biology. Imaging
Image Processing with ImageJ 1. Spatial filters Outlines background correction image denoising edges detection 2. Fourier domain filtering correction of periodic artefacts 3. Binary operations masks morphological
More informationSGN1158 Introduction to Signal Processing Test. Solutions
SGN1158 Introduction to Signal Processing Test. Solutions 1. Convolve the function ( ) with itself and show that the Fourier transform of the result is the square of the Fourier transform of ( ). (Hints:
More informationPerformance Verification of SuperResolution Image Reconstruction
Performance Verification of SuperResolution Image Reconstruction Masaki Sugie Department of Information Science, Kogakuin University Tokyo, Japan Email: em13010@ns.kogakuin.ac.jp Seiichi Gohshi Department
More informationHow an electronic shutter works in a CMOS camera. First, let s review how shutters work in film cameras.
How an electronic shutter works in a CMOS camera I have been asked many times how an electronic shutter works in a CMOS camera and how it affects the camera s performance. Here s a description of the way
More informationLecture 14. Point Spread Function (PSF)
Lecture 14 Point Spread Function (PSF), Modulation Transfer Function (MTF), Signaltonoise Ratio (SNR), Contrasttonoise Ratio (CNR), and Receiver Operating Curves (ROC) Point Spread Function (PSF) Recollect
More informationIntroduction Bilateral Filtering Results. Bilateral Filtering. Mathias Eitz. TU Berlin. November, 21st 2006
Introduction TU Berlin November, 21st 2006 About Me Introduction Student at TU Berlin since 2002 eitz@cs.tuberlin.de Outline Introduction 1 Introduction Smoothing Filters Comparison 2 Intuition Mathematical
More informationCHAPTER 3: DIGITAL IMAGING IN DIAGNOSTIC RADIOLOGY. 3.1 Basic Concepts of Digital Imaging
Physics of Medical XRay Imaging (1) Chapter 3 CHAPTER 3: DIGITAL IMAGING IN DIAGNOSTIC RADIOLOGY 3.1 Basic Concepts of Digital Imaging Unlike conventional radiography that generates images on film through
More informationUnderstanding astigmatism Spring 2003
MAS450/854 Understanding astigmatism Spring 2003 March 9th 2003 Introduction Spherical lens with no astigmatism Crossed cylindrical lenses with astigmatism Horizontal focus Vertical focus Plane of sharpest
More informationRodenstock Photo Optics
Rogonar RogonarS Rodagon ApoRodagon N RodagonWA ApoRodagonD Accessories: ModularFocus Lenses for Enlarging, CCD Photos and Video To reproduce analog photographs as pictures on paper requires two
More informationHigh Performance GPUbased Preprocessing for TimeofFlight Imaging in Medical Applications
High Performance GPUbased Preprocessing for TimeofFlight Imaging in Medical Applications Jakob Wasza 1, Sebastian Bauer 1, Joachim Hornegger 1,2 1 Pattern Recognition Lab, FriedrichAlexander University
More informationSampling and Interpolation. Yao Wang Polytechnic University, Brooklyn, NY11201
Sampling and Interpolation Yao Wang Polytechnic University, Brooklyn, NY1121 http://eeweb.poly.edu/~yao Outline Basics of sampling and quantization A/D and D/A converters Sampling Nyquist sampling theorem
More informationImage Formation. 7year old s question. Reference. Lecture Overview. It receives light from all directions. Pinhole
Image Formation Reerence http://en.wikipedia.org/wiki/lens_(optics) Reading: Chapter 1, Forsyth & Ponce Optional: Section 2.1, 2.3, Horn. The slides use illustrations rom these books Some o the ollowing
More informationWhy pinhole? Long exposure times. Timeless quality. Depth of field. Limitations lead to freedom
Why pinhole? One of the best things about pinhole photography is its simplicity. Almost any container that can be made lighttight can be turned into a pinhole camera. Building your own camera is not only
More informationCSE168 Computer Graphics II, Rendering. Spring 2006 Matthias Zwicker
CSE168 Computer Graphics II, Rendering Spring 2006 Matthias Zwicker Last time Global illumination Light transport notation Path tracing Sampling patterns Reflection vs. rendering equation Reflection equation
More informationImage Enhancement: Frequency domain methods
Image Enhancement: Frequency domain methods The concept of filtering is easier to visualize in the frequency domain. Therefore, enhancement of image f ( m, n) can be done in the frequency domain, based
More informationPHYS 39a Lab 3: Microscope Optics
PHYS 39a Lab 3: Microscope Optics Trevor Kafka December 15, 2014 Abstract In this lab task, we sought to use critical illumination and Köhler illumination techniques to view the image of a 1000 linesperinch
More informationRevision problem. Chapter 18 problem 37 page 612. Suppose you point a pinhole camera at a 15m tall tree that is 75m away.
Revision problem Chapter 18 problem 37 page 612 Suppose you point a pinhole camera at a 15m tall tree that is 75m away. 1 Optical Instruments Thin lens equation Refractive power Cameras The human eye Combining
More information07 SAMPLING AND RECONSTRUCTION
07 SAMPLING AND RECONSTRUCTION Although the final output of a renderer like pbrt is a twodimensional grid of colored pixels, incident radiance is actually a continuous function defined over the film plane.
More information4.3 AnalogtoDigital Conversion
4.3 AnalogtoDigital Conversion overview including timing considerations block diagram of a device using a DAC and comparator example of a digitized spectrum number of data points required to describe
More informationHigh Quality Image Deblurring Panchromatic Pixels
High Quality Image Deblurring Panchromatic Pixels ACM Transaction on Graphics vol. 31, No. 5, 2012 Sen Wang, Tingbo Hou, John Border, Hong Qin, and Rodney Miller Presented by BongSeok Choi School of Electrical
More informationSampling Theorem Notes. Recall: That a time sampled signal is like taking a snap shot or picture of signal periodically.
Sampling Theorem We will show that a band limited signal can be reconstructed exactly from its discrete time samples. Recall: That a time sampled signal is like taking a snap shot or picture of signal
More informationChapter 23. The Refraction of Light: Lenses and Optical Instruments
Chapter 23 The Refraction of Light: Lenses and Optical Instruments Lenses Converging and diverging lenses. Lenses refract light in such a way that an image of the light source is formed. With a converging
More informationThe Limits of Human Vision
The Limits of Human Vision Michael F. Deering Sun Microsystems ABSTRACT A model of the perception s of the human visual system is presented, resulting in an estimate of approximately 15 million variable
More informationTheremino System Theremino Spectrometer Technology
Theremino System Theremino Spectrometer Technology theremino System  Theremino Spectrometer Technology  August 15, 2014  Page 1 Operation principles By placing a digital camera with a diffraction grating
More informationIntroduction to Medical Imaging. Lecture 11: ConeBeam CT Theory. Introduction. Available conebeam reconstruction methods: Our discussion:
Introduction Introduction to Medical Imaging Lecture 11: ConeBeam CT Theory Klaus Mueller Available conebeam reconstruction methods: exact approximate algebraic Our discussion: exact (now) approximate
More informationPROPERTIES OF THIN LENSES. Paraxialray Equations
PROPERTIES OF THIN LENSES Object: To measure the focal length of lenses, to verify the thin lens equation and to observe the more common aberrations associated with lenses. Apparatus: PASCO Basic Optical
More informationComputational Optical Imaging  Optique Numerique.  Deconvolution 
Computational Optical Imaging  Optique Numerique  Deconvolution  Winter 2014 Ivo Ihrke Deconvolution Ivo Ihrke Outline Deconvolution Theory example 1D deconvolution Fourier method Algebraic method
More informationDigital Image Requirements for New Online US Visa Application
Digital Image Requirements for New Online US Visa Application As part of the electronic submission of your DS160 application, you will be asked to provide an electronic copy of your photo. The photo must
More informationToday. next two weeks
Today Temporal and spatial coherence Spatially incoherent imaging The incoherent PSF The Optical Transfer Function (OTF) and Modulation Transfer Function (MTF) MTF and contrast comparison of spatially
More informationAbout the Use of Digital Single Lens Reflex Cameras on Microscopes by Jan Hinsch
www.modernmicroscopy.com: "how to" tutorial series About the Use of Digital Single Lens Reflex Cameras on Microscopes by Jan Hinsch 2/2/2004 For micrography a choice between dedicated microscope cameras
More informationGeometric Optics Converging Lenses and Mirrors Physics Lab IV
Objective Geometric Optics Converging Lenses and Mirrors Physics Lab IV In this set of lab exercises, the basic properties geometric optics concerning converging lenses and mirrors will be explored. The
More informationInvestigation of Color Aliasing of High Spatial Frequencies and Edges for BayerPattern Sensors and Foveon X3 Direct Image Sensors
Investigation of Color Aliasing of High Spatial Frequencies and Edges for BayerPattern Sensors and Foveon X3 Direct Image Sensors Rudolph J. Guttosch Foveon, Inc. Santa Clara, CA Abstract The reproduction
More information1051232 Imaging Systems Laboratory II. Laboratory 4: Basic Lens Design in OSLO April 2 & 4, 2002
05232 Imaging Systems Laboratory II Laboratory 4: Basic Lens Design in OSLO April 2 & 4, 2002 Abstract: For designing the optics of an imaging system, one of the main types of tools used today is optical
More informationEXPERIMENT 6 OPTICS: FOCAL LENGTH OF A LENS
EXPERIMENT 6 OPTICS: FOCAL LENGTH OF A LENS The following website should be accessed before coming to class. Text reference: pp189196 Optics Bench a) For convenience of discussion we assume that the light
More informationHigh Dynamic Range Video Using Split Aperture Camera
High Dynamic Range Video Using Split Aperture Camera Hongcheng Wang, Ramesh Raskar, Narendra Ahuja Beckman Institute, University of Illinois at UrbanaChampaign (UIUC), IL, USA Mitsubishi Electric Research
More informationUnderstanding Exposure for Better Photos Now
Understanding Exposure for Better Photos Now Beginner Photography Tutorials Created exclusively for Craftsy by Nicholas Donner TABLE OF CONTENTS 01 02 05 07 10 12 Meet the Expert Shutter Speed Aperture
More informationFrom Pixel to InfoCloud News at Leica Geosystems JACIE Denver, 31 March 2011 Ruedi Wagner Hexagon Geosystems, Geospatial Solutions Division.
From Pixel to InfoCloud News at Leica Geosystems JACIE Denver, 31 March 2011 Ruedi Wagner Hexagon Geosystems, Geospatial Solutions Division What else can I do with my sensor/data? Earth to Image Image
More informationCamera Lenses and Focal Length
Camera Lenses and Focal Length In Photography, your lens is often your most important purchase. This photography tutorial outlines some important qualities of different lenses, and how each performs in
More informationChoosing a digital camera for your microscope John C. Russ, Materials Science and Engineering Dept., North Carolina State Univ.
Choosing a digital camera for your microscope John C. Russ, Materials Science and Engineering Dept., North Carolina State Univ., Raleigh, NC One vital step is to choose a transfer lens matched to your
More informationDigital Image Fundamentals. Selim Aksoy Department of Computer Engineering Bilkent University saksoy@cs.bilkent.edu.tr
Digital Image Fundamentals Selim Aksoy Department of Computer Engineering Bilkent University saksoy@cs.bilkent.edu.tr Imaging process Light reaches surfaces in 3D. Surfaces reflect. Sensor element receives
More informationA Beginner's Guide to Simple Photography Concepts: ISO, Aperture, Shutter Speed Depth of Field (DOF) and Exposure Compensation
A Beginner's Guide to Simple Photography Concepts: ISO, Aperture, Shutter Speed Depth of Field (DOF) and Exposure Compensation There are 3 things that affect your image quality in photography; ISO, Aperture
More informationFilters for Digital Photography
Filters for Digital Photography LICHTFILTER Whether for analog or Digital Photography: The best results are achieved by using correction filters  not by digitally enhancing in a software program as once
More informationSOFTWARE FOR GENERATION OF SPECTRUM COMPATIBLE TIME HISTORY
3 th World Conference on Earthquake Engineering Vancouver, B.C., Canada August 6, 24 Paper No. 296 SOFTWARE FOR GENERATION OF SPECTRUM COMPATIBLE TIME HISTORY ASHOK KUMAR SUMMARY One of the important
More informationAdvanced Computer Graphics. Rendering Equation. Matthias Teschner. Computer Science Department University of Freiburg
Advanced Computer Graphics Rendering Equation Matthias Teschner Computer Science Department University of Freiburg Outline rendering equation Monte Carlo integration sampling of random variables University
More informationResolution Enhancement of Photogrammetric Digital Images
DICTA2002: Digital Image Computing Techniques and Applications, 2122 January 2002, Melbourne, Australia 1 Resolution Enhancement of Photogrammetric Digital Images John G. FRYER and Gabriele SCARMANA
More informationCSE 167: Lecture #3: Projection. Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011
CSE 167: Introduction to Computer Graphics Lecture #3: Projection Jürgen P. Schulze, Ph.D. University of California, San Diego Fall Quarter 2011 Announcements Project 1 due Friday September 30 th, presentation
More informationSuperresolution images reconstructed from aliased images
Superresolution images reconstructed from aliased images Patrick Vandewalle, Sabine Süsstrunk and Martin Vetterli LCAV  School of Computer and Communication Sciences Ecole Polytechnique Fédérale de Lausanne
More informationAntennas. Antenna Design Kit. M. Kesteven ATNF 25/September/2001. The primary elements of a synthesis array. The Antenna Structure
Antennas The Antenna Structure The primary elements of a synthesis array M. Kesteven ATNF 25/September/2001 * Backup structure * Reflector surface(s) shape accuracy construction * Two axis Mount Antenna
More informationSIGNAL PROCESSING & SIMULATION NEWSLETTER
1 of 10 1/25/2008 3:38 AM SIGNAL PROCESSING & SIMULATION NEWSLETTER Note: This is not a particularly interesting topic for anyone other than those who ar e involved in simulation. So if you have difficulty
More informationPersonal Identity Verification (PIV) IMAGE QUALITY SPECIFICATIONS FOR SINGLE FINGER CAPTURE DEVICES
Personal Identity Verification (PIV) IMAGE QUALITY SPECIFICATIONS FOR SINGLE FINGER CAPTURE DEVICES 1.0 SCOPE AND PURPOSE These specifications apply to fingerprint capture devices which scan and capture
More informationFAST Fourier Transform (FFT) and Digital Filtering Using LabVIEW
FAST Fourier Transform (FFT) and Digital Filtering Using LabVIEW Wei Lin Department of Biomedical Engineering Stony Brook University Instructor s Portion Summary This experiment requires the student to
More informationAgilent Time Domain Analysis Using a Network Analyzer
Agilent Time Domain Analysis Using a Network Analyzer Application Note 128712 0.0 0.045 0.6 0.035 Cable S(1,1) 0.4 0.2 Cable S(1,1) 0.025 0.015 0.005 0.0 1.0 1.5 2.0 2.5 3.0 3.5 4.0 Frequency (GHz) 0.005
More informationMoving Average Filters
CHAPTER 15 Moving Average Filters The moving average is the most common filter in DSP, mainly because it is the easiest digital filter to understand and use. In spite of its simplicity, the moving average
More informationA Realistic Camera Model for Computer Graphics
A Realistic Camera Model for Computer Graphics Craig Kolb Computer Science Department Princeton University Don Mitchell Advanced Technology Division Microsoft Pat Hanrahan Computer Science Department Stanford
More informationCamera calibration and epipolar geometry. Odilon Redon, Cyclops, 1914
Camera calibration and epipolar geometry Odilon Redon, Cyclops, 94 Review: Alignment What is the geometric relationship between pictures taken by cameras that share the same center? How many points do
More informationBlind Deconvolution of Barcodes via Dictionary Analysis and Wiener Filter of Barcode Subsections
Blind Deconvolution of Barcodes via Dictionary Analysis and Wiener Filter of Barcode Subsections Maximilian Hung, Bohyun B. Kim, Xiling Zhang August 17, 2013 Abstract While current systems already provide
More informationDigital Photography Composition. Kent Messamore 9/8/2013
Digital Photography Composition Kent Messamore 9/8/2013 Photography Equipment versus Art Last week we focused on our Cameras Hopefully we have mastered the buttons and dials by now If not, it will come
More informationBasic Acoustics and Acoustic Filters
Basic CHAPTER Acoustics and Acoustic Filters 1 3 Basic Acoustics and Acoustic Filters 1.1 The sensation of sound Several types of events in the world produce the sensation of sound. Examples include doors
More informationFrequency domain filtering fundamentals
Frequency domain filtering fundamentals by Gleb V. Tcheslavski: gleb@ee.lamar.edu http://ee.lamar.edu/gleb/dip/index.htm Spring 2008 ELEN 4304/5365 DIP 1 Preliminaries For a digital image f(x,y) the basic
More informationUnderstanding camera tradeoffs through a Bayesian analysis of light field projections
Understanding camera tradeoffs through a Bayesian analysis of light field projections Anat Levin William T. Freeman Frédo Durand Massachusetts Institute of Technology Computer Science and Artificial Intelligence
More informationCorrelation and Convolution Class Notes for CMSC 426, Fall 2005 David Jacobs
Correlation and Convolution Class otes for CMSC 46, Fall 5 David Jacobs Introduction Correlation and Convolution are basic operations that we will perform to extract information from images. They are in
More informationDICOM Correction Item
Correction Number DICOM Correction Item CP626 Log Summary: Type of Modification Clarification Rationale for Correction Name of Standard PS 3.3 2004 + Sup 83 The description of pixel spacing related attributes
More informationRodenstock Photo Optics
ApoSironarS ApoMacroSironar ApoGrandagon GrandagonN Accessories: Center filters Accessories: FocusMount Lenses for Analog Professional Photography Even in the age of digital photography, the professional
More informationMedical Image Processing on the GPU. Past, Present and Future. Anders Eklund, PhD Virginia Tech Carilion Research Institute andek@vtc.vt.
Medical Image Processing on the GPU Past, Present and Future Anders Eklund, PhD Virginia Tech Carilion Research Institute andek@vtc.vt.edu Outline Motivation why do we need GPUs? Past  how was GPU programming
More informationHigh Dynamic Range Imaging
High Dynamic Range Imaging Cecilia Aguerrebere Advisors: Julie Delon, Yann Gousseau and Pablo Musé Télécom ParisTech, France Universidad de la República, Uruguay High Dynamic Range Imaging (HDR) Capture
More informationSchneider Kreuznach PC Tilt/Shift Lenses
User Manual PCTS SUPERANGULON 2.8/50 HM PCTS MAKROSYMMAR 4.5/90 HM with interchangeable bayonet mount for Canon EOS, Nikon, Pentax K or Sony Alpha PCTS APODIGITAR 5.6/120 HM Aspheric with bayonet
More informationLecture 16: A Camera s Image Processing Pipeline Part 1. Kayvon Fatahalian CMU 15869: Graphics and Imaging Architectures (Fall 2011)
Lecture 16: A Camera s Image Processing Pipeline Part 1 Kayvon Fatahalian CMU 15869: Graphics and Imaging Architectures (Fall 2011) Today (actually all week) Operations that take photons to an image Processing
More informationPhysics 6C. Cameras and the Human Eye
Physics 6C Cameras and the Human Eye CAMERAS A typical camera uses a converging lens to focus a real (inverted) image onto photographic film (or in a digital camera the image is on a CCD chip). (Picture
More informationT = 1 f. Phase. Measure of relative position in time within a single period of a signal For a periodic signal f(t), phase is fractional part t p
Data Transmission Concepts and terminology Transmission terminology Transmission from transmitter to receiver goes over some transmission medium using electromagnetic waves Guided media. Waves are guided
More informationExperiment 3 Lenses and Images
Experiment 3 Lenses and Images Who shall teach thee, unless it be thine own eyes? Euripides (480?406? BC) OBJECTIVES To examine the nature and location of images formed by es. THEORY Lenses are frequently
More informationHuman visual perception  topics. Anatomy of the human eye
Human visual perception  topics Visual acuity WeberFechner Law Lateral inhibition and excitation Transfer functions of the color channels Spatial and temporal masking Eye movements Bernd Girod: EE368b
More informationBasic Manual Control of a DSLR Camera
Basic Manual Control of a DSLR Camera Naixn 2008 Photographers don t just take photographs  they make them! Produced by Yon Ankersmit for curiouseye.com 2009 Digital Single Lens Reflex Camera The basic
More informationTo determine vertical angular frequency, we need to express vertical viewing angle in terms of and. 2tan. (degree). (1 pt)
Polytechnic University, Dept. Electrical and Computer Engineering EL6123  Video Processing, S12 (Prof. Yao Wang) Solution to Midterm Exam Closed Book, 1 sheet of notes (double sided) allowed 1. (5 pt)
More informationHybrid 5D Fourier transform  a flexible tool for land data interpolation Juefu Wang and Shaowu Wang, CGG
Hybrid 5D Fourier transform  a flexible tool for land data interpolation Juefu Wang and Shaowu Wang, CGG Summary We present an interpolation method based on a hybrid 5D Fourier transform, which combines
More informationCone Beam Reconstruction Jiang Hsieh, Ph.D.
Cone Beam Reconstruction Jiang Hsieh, Ph.D. Applied Science Laboratory, GE Healthcare Technologies 1 Image Generation Reconstruction of images from projections. textbook reconstruction advanced acquisition
More informationRadiometric alignment and vignetting calibration. Pablo d'angelo University of Bielefeld
Radiometric alignment and vignetting calibration University of Bielefeld Overview Motivation Image formation Vignetting and exposure estimation Results Summary Motivation Determination of vignetting and
More informationFILTER CIRCUITS. A filter is a circuit whose transfer function, that is the ratio of its output to its input, depends upon frequency.
FILTER CIRCUITS Introduction Circuits with a response that depends upon the frequency of the input voltage are known as filters. Filter circuits can be used to perform a number of important functions in
More informationShutter Speed in Digital Photography
Shutter Speed in Digital Photography [Notes from Alan Aldrich as presented to the Hawkesbury Camera Club in April 2014] Light is a form of energy and as such behaves as formulated in the general power
More information2) A convex lens is known as a diverging lens and a concave lens is known as a converging lens. Answer: FALSE Diff: 1 Var: 1 Page Ref: Sec.
Physics for Scientists and Engineers, 4e (Giancoli) Chapter 33 Lenses and Optical Instruments 33.1 Conceptual Questions 1) State how to draw the three rays for finding the image position due to a thin
More informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
Exam Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) A single slit forms a diffraction pattern, with the first minimum at an angle of 40 from
More informationScan Time Reduction and Xray Scatter Rejection in Dual Modality Breast Tomosynthesis. Tushita Patel 4/2/13
Scan Time Reduction and Xray Scatter Rejection in Dual Modality Breast Tomosynthesis Tushita Patel 4/2/13 Breast Cancer Statistics Second most common cancer after skin cancer Second leading cause of cancer
More informationIntroduction to Digital Filters
CHAPTER 14 Introduction to Digital Filters Digital filters are used for two general purposes: (1) separation of signals that have been combined, and (2) restoration of signals that have been distorted
More informationNote it they ancients had known Newton s first law, the retrograde motion of the planets would have told them that the Earth was moving.
6/24 Discussion of the first law. The first law appears to be contained within the second and it is. Why state it? Newton s laws are not always valid they are not valid in, say, an accelerating automobile.
More informationUsing Photorealistic RenderMan for HighQuality Direct Volume Rendering
Using Photorealistic RenderMan for HighQuality Direct Volume Rendering Cyrus Jam cjam@sdsc.edu Mike Bailey mjb@sdsc.edu San Diego Supercomputer Center University of California San Diego Abstract With
More informationRendering. Clay Render : This is used for checking the lighting without worrying about the materials. Advanced Settings:
Advanced Settings: Clay Render : This is used for checking the lighting without worrying about the materials. The Clay Render is a way of saying check the lighting without materials/textures. It is useful
More informationPurpose of Time Series Analysis. Autocovariance Function. Autocorrelation Function. Part 3: Time Series I
Part 3: Time Series I Purpose of Time Series Analysis (Figure from Panofsky and Brier 1968) Autocorrelation Function Harmonic Analysis Spectrum Analysis Data Window Significance Tests Some major purposes
More informationThe Fundamentals of MTF, Wiener Spectra, and DQE. Motivation
The Fundamentals of MTF, Wiener Spectra, and DQE Robert M Nishikawa Kurt Rossmann Laboratories for Radiologic Image Research Department of Radiology, The University of Chicago Motivation Goal of radiology:
More information