Study and Implementation of Video Compression Standards (H.264/AVC and Dirac)

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1 Project Proposal Study and Implementation of Video Compression Standards (H.264/AVC and Dirac) Sumedha Phatak Objective: A study, implementation and comparison of the baseline profiles of H.264/AVC and Dirac will be carried out based on factors like video quality, bit rates, compression ratio, complexity and performance analysis. Different test video sequences will be used to compare these two standards on quality parameters like SSIM [13], MSE [13] and PSNR [13] at various bit rates using the MSU video quality measurement tool (MSU VQMT) [14]. Tool to be used MSU-VQMT [14]: Important Video Quality Measurement Terms: Structural similarity metric (SSIM) [13]: This index is a method for measuring the similarity between two frames. It is a full reference metric, or in other words, the measuring of image quality is done using an initial uncompressed or distortion-free frame as reference. Mean squared error (MSE) [13]: The MSE is computed by averaging the squared intensity differences of the distorted and reference image/frame pixels. Two distorted images with the

2 same MSE may have very different types of errors, some of which are much more visible than others. Peak signal-to-noise ratio (PSNR) [13]: The PSNR is most commonly used as a measure of quality of reconstruction of compression codecs. The signal in this case is the maximum value of the pixels and the noise is the error introduced by compression.

3 Introduction: Digital video compression techniques have played an important role in the world of telecommunication and multimedia systems where bandwidth is still a valuable commodity. [1] In general, data compression or video/image compression means bit-rate reduction and it involves encoding information using fewer bits than the original representation. Compression can be either lossy or lossless. [1] The former reduces bits by eliminating statistical redundancy and no information is lost in this type of compression whereas, the latter by identifying and removing marginally important information. [9] Most of the video compression techniques are lossy in nature. And in this type of compression, there is a tradeoff between video qualities, cost of processing the compression and decompression, and system requirements. [1] Video compression uses modern coding techniques to reduce redundancy in video data. Most video compression algorithms and codecs [1] combine spatial image compression and temporal motion compensation. [9] Today, nearly all commonly used video compression methods (e.g., those in standards approved by the ITU-T or ISO) [3] apply a discrete cosine transform (DCT) [20] for spatial redundancy reduction. Other methods, such as fractal compression, matching pursuit and the use of a discrete wavelet transform (DWT) [11] have been the subject of some research, but are typically not used in practical products (except for the use of wavelet coding as still-image coders without motion compensation).[18] Table 1 [1] shows the evolution of the various video compression standards. Table 1: History of video compression standards [1]

4 Figure 1[2] shows an easier graphical presentation separating the ITU-T and ISO based [15] compression standards: Figure 1: Evolution of video compression standards [2] H.264/AVC [3], Dirac [6] and AVS China [3] are among the latest video coding standards by ISO/ITU-T/IEC, ISO/BBC and China standards organization [3]. H.264 [3] H.264/MPEG-4 Part 10 or AVC (advanced video coding) is a standard for video compression [3], and is currently one of the most commonly used formats for the recording, compression, and distribution of high definition video. This was mainly intended to create a standard capable of providing good video quality at substantially lower bit rates than previous standards (i.e., half or less the bit rate of MPEG-2, H.263, or MPEG-4 Part 2) [4], without significantly increasing the complexity of design.[3] Figure 2 [2] shows the H.264 architecture.

5 Figure 2: H.264 architecture [2] Figures 3[4] and 4 [4] show the block diagrams for the H.264 encoder and H.264 decoder respectively. Figure 3: H.264 encoder block diagram [4]

6 Dirac [6] Figure 4: H.264 decoder block diagram [4] It is an open and free video compression format developed by BBC research. It is mainly intended to provide high quality video compression for applications like Ultra HDTV. It mainly competes with existing standards like H.264 [5] and VC-1 [12]. Dirac[6] is a hybrid video codec because it involves both transform and motion compensation. Motion compensation is used to remove any temporal redundancy in data and transform is used to remove the spatial redundancy. [10] Dirac uses modern techniques like, wavelet transform and arithmetic coding for entropy coding [16]. The image motion is tracked and the motion information is used to make a prediction of a later frame. A wavelet transform [16] is applied to the predicted frame and the transform coefficients are quantized and entropy coded. [10] The applications of Dirac range from high definition television (HDTV) to web streaming due to its flexibility. Dirac compresses pictures from low resolution of pixels (QCIF) to (HDTV).However, Dirac promises improvements in quality and significant amount of savings in data rate over other codecs like H.264/VC-1. [6] Figures 5[5] and 6[5] show the Dirac encoder and decoder block diagrams respectively.

7 Figure 5: Dirac encoder block diagram [5] Figure 6: Dirac decoder block diagram [5]

8 Abbreviations and Acronyms: AVC: Advanced Video Coding AVS: Audio Video Standard BBC: British Broadcasting Corporation CIF: Common Intermediate Format CODEC: Coder and Decoder DCT: Discrete Cosine Transform HDTV: High-Definition Television IEC: International Electrotechnical Commission ISO: International Organization for Standardization ITU-T: International Telecommunication Union - Telecommunication Standardization sector JPEG: Joint Photographic Experts Group MPEG: Moving Picture Experts Group MSE: Mean Square Error MSU: Moscow State University PSNR: Peak Signal to Noise ratio QCIF: Quarter Common Intermediate Format SMPTE: Society of Motion Picture and Television Engineers SSIM: Structural Similarity Metric VQMT: Video Quality Measurement Tool

9 References: [1]Video compression standards history: [2] Video conferencing standards and technology. [3] K. R. Rao and D. N. Kim, Current video coding standards: H.264/AVC, Dirac, AVS China and VC-1, IEEE 42nd Southeastern symposium on system theory (SSST), March , pp. 1-8, March [4] S. Kwon, A. Tamhankar and K.R. Rao, Overview of H.264 / MPEG-4 Part 10, J. Visual Communication and Image Representation, vol. 17, pp , April [5]T. Borer and T. Davies, Dirac video compression using open technology, BBC EBU Technical Review, July [6] A. Ravi, and K.R. Rao, Performance analysis and comparison of the dirac video codec with H.264/MPEG-4 Part 10 AVC, International Journal of Wavelets, Multiresolution and Information Processing, vol.4, pp , January [7] T. Wiegand, and G. Sullivan, Overview of H.264/AVC video coding standards, IEEE Transactions on circuits and systems for video technology, vol. 13, no. 7,pp , July [8]DiracSpecification,Version2.2.3,Available: -spec-latest.pdf [9] General information on Data/ Video compression [10] The Dirac web page: [11] S.-T. Hsiang, A new subband/wavelet framework for AVC/H.264 intraframe coding and performance comparison with motion-jpeg 2000", SPIE/VCIP, vol.6822, pp P-1 through 12, Jan [12] VC-1 Compressed video bit stream format and decoding process (SMPTE 421M-2006), SMPTE standard, pp. 2-9, [13] Z. Wang, et al, Image quality assessment: From error visibility to structural similarity, IEEE Transactions on Image Processing, vol.13, no.4, pp , April [14] MSU Video quality measurement tool:

10 [15] G. J. Sullivan and J. Ohm, Recent developments in standardization of high efficiency video coding (HEVC), Proc. SPIE 7798, 77980V (2010) [16] Dirac developer support documentation: [17] I. Richardson, The H.264 advanced video compression standard, Wiley, 2 nd edition, [18] C. Christopoulos, A. Skodras, T.Ebrahimi, The JPEG2000 still image coding system: An Overview, IEEE Trans. on Consumer Electronics, vol.46, pp , Nov [19] B. Zeng and J. Fu, Directional discrete cosine transforms - A new framework for image coding, IEEE Trans. on Circuits and Systems for Video Technology, vol. 18, no. 3, pp , Mar [20] K. R. Rao and P. Yip, Discrete Cosine Transform: Algorithms, Advantages, Applications (Academic Press, Boston, 1990). [21] A. Ravi, Performance analysis and comparison of the dirac video codec with H.264/ MPEG 4 Part 10 AVC, M.S thesis, EE dept., UT Arlington, Aug 2009 [22]JM software source code:

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