臺灣博碩士論文加值系統

對一般的視訊應用而言，通常視訊源只需編碼一次，再把壓縮後的資料以各種媒介傳送到每個用戶端解碼，因此為了減低消費者的成本，解碼器要盡可能的簡單，而傳統的視訊規格 (MPEG-X，H.26X)剛好符合此視訊應用的需求。然而近年來感測網路、視訊監控…等，這些視訊應用需要數量較多的編碼器及較少的解碼器，因此使用傳統的視訊規格會使得整體成本大幅上升。為了減低成本，把複雜度從編碼端轉移到解碼端成為一個重要的議題。而Wyner-Ziv視訊編碼為近年來對這個需求所提出的一個有效編碼架構。
一般的Wyner-Ziv視訊編碼架構都是以框架 (frame) 為單位，在一個GOP (Group of Picture) 內把視訊框架分成Wyner-Ziv框架和INTRA框架兩種類型。本篇論文提出以區塊 (block) 為單位來實現Wyner-Ziv視訊編碼的架構，我們會根據視訊內容來安排Wyner-Ziv區塊和INTRA區塊。因此空間上的每個區塊位置都有自己的INTRA週期，我們把此週期稱為時域區塊群 (TGOB)，利用此概念我們可以同時把時間軸和空間軸上的冗餘消除。此外，由於每個區塊的TGOB都不相同，為了產生輔助資訊 (side information)，每個區塊都需要未來的INTRA區塊，所以此架構的緩衝暫存器 (buffer) 會比傳統方法大，但是其計算複雜度不會上升。實驗結果顯示，在較靜態的視訊內容中，我們方法的RD performance 在正常工作區中(PSNR介於35dB~45dB) 和一般框架為單位的編碼架構相比，可以達到4~6dB的增益，但對於較動態的視訊內容，其RD performance並沒有明顯的增加。因此，可以合理地應用於視訊監控等具備靜態背景及固定攝影機等應用中。

For most general applications, video data need to be encoded once, and transmitted to clients via diverse transmission media. In order to reduce the cost, the decoder has to be as simple as possible. Traditional video standards (MPEG-X, H.26X) are suitable for this kind of video applications. However, there are some other applications, such as sensor network, video surveillance, etc, which require more number of encoders and fewer decoders. The cost will obviously increase if the traditional video standards are applied. In order to reduce the cost, transferring the complexity from encoder side to decoder side becomes a feasible and important issue. Wyner-Ziv (WZ) video coding, being an effective coding architecture, is proposed to fit this purpose.
The general WZ video coding architecture is frame-based; it classifies each frame in a GOP (Group of Picture) into types of WZ- or intra-coded. In this thesis, WZ video coding is fulfilled in block-based architecture. We arrange WZ blocks and intra blocks according to video contents. Co-located blocks in the temporal direction are dynamically grouped, called Temporal Group of Block (TGOB). Specially, the boundary blocks of a TGOB are intra-coded while others there-between are WZ-coded. According to this concept, the redundancies in both the temporal and the spatial directions can be eliminated. Experiments show that our proposed scheme has an RD performance gain of 4~6 dB for static video contents in common working region (PSNR between 35dB~45dB). However, the gains become insignificant for video contents with larger motion. Therefore, our proposed technique is promising in application of video surveillance with static backgrounds and fixed cameras.

Chapter 1: Introduction 1
1.1 Motivation 1
1.2 Groundwork of Distributed Video Coding 1
1.2.1 Slepian-Wolf Theorem 2
1.2.2 Wyner-Ziv Theorem 5
1.2.3 Wyner-Ziv Codec Construction with Slepian-Wolf Theorem 5
1.3 Literature Survey 7
1.4 Thesis Outline 9
Chapter 2: Conventional Wyner-Ziv Video Coding Architecture 10
2.1 Pixel-Domain Wyenr-Ziv Video Codec 10
2.2 Transform-Domain Wyenr-Ziv Video Codec 16
2.3 Wavelet-Domain Wyenr-Ziv Video Codec 19
Chapter 3: Wyner-Ziv Video Coding Technique Based on Temporally Dynamic Key Block Decision 21
3.1 Overview of Our Proposed Key-Block-Based Wyner-Ziv Video Coding 24
3.2 Details of the Proposed Scheme 25
3.2.1 Block-Mode Decision Unit 27
3.2.1 WZ Frame Generator 28
3.2.3 LDPC Coding and Decoding 29
3.2.4 Side Information Generator 30
3.2.5 LDPC Buffer and Decoded Key Block Queue 30
3.3 Modified Scheme to Achieve Higher Quality 32
Chapter 4: Experimental Results 34
4.1 Channel Coding Performance of Inserting Zeros to Form WZ Frames 34
4.2 Performance of the Proposed Pixel-Domain WZ Video Codec 39
4.3 Performance of the Modified WZ Video Codec for Higher Quality 47
Chapter 5: Conclusions and Future Work 52
5.1 Conclusions 52
5.2 Future Work 53
REFERENCES 54
PUBLICATIONS 58

[1] D. Slepian and J. K. Wolf, “Noiseless coding of correlated information sources,” IEEE Trans. on Information Theory, Vol. 19, no. 4, p.p. 471-480, July 1973.
[2] D. Wyner and J. Ziv, “The rate-distortion function for source coding with side information at the decoder,” IEEE Trans. on Information Theory, Vol. 22, pp. 1-10, Jan. 1976.
[3] A. Aaron and B. Girod, “Compression with side information using turbo codes,” Proc. of IEEE Data Compression Conf. (DCC), Snowbird, UT, pp. 252-261, April 2-4, 2002.
[4] D. Varodayan, A. Aaron, and B. Girod, “Rate-adaptive codes for distributed source coding,” EURASIP Signal Processing, no. 86, pp. 3123-3130, November 2006.
[5] Q. Xu, V. Stankovic, and Z. Xiong, “Distributed source-channel coding of video using raptor codes,” IEEE JSAC on Cross-Layer Optimized Wireless Multimedia Communications, vol. 25, May 2007.
[6] A. Aaron, R. Zhang and B. Girod, ”Wyner-Ziv coding of motion video,” 36th Asilomar Conf. on Signals, Systems and Computer, Pacific Grove, USA, November 2002.
[7] B. Girod, A. Aaron, S. Rane, D. Rebollo-Monedero, “Distributed video coding,” Proceedings of IEEE, vol. 93, no. 1, pp. 71-83, January 2005.
[8] A. Aaron, S. Rane, and B. Girod, “Transform-domain Wyner-Ziv codec for video,” Proc. of SPIE Visual Communications and Image Processing (VCIP), Santa Clara, CA, January 2004.
[9] C. Brites, J. Ascenso, F. Pereira, “Improving transform domain Wyner-Ziv video coding performance,” Proc. of IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Toulouse, France, May 14-19, 2006.
[10] Y. Tonomura, and T. Nakachi, “A new framework for distributed video coding based on JPEG 2000,” Proc. of IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Toulouse, France, May 14-19, 2006.
[11] X. Guo, Y. Lu, F. Wu, W. Gao, “Distributed video coding using wavelet,” Proc. of IEEE Int’l Conf. on Circuits and Systems (ISCAS), Island of Kos, Greece, May 2006.
[12] J. Ascenso, C. Brites, and F. Pereira, “Improving frame interpolation with spatial motion smoothing for pixel domain distributed video coding,” 5th EURASIP Conf. on Speech and Image Processing, Multimedia Communications and Services, Slovak Republic, June 29 – July 2, 2005.
[13] J. Ascenso, C. Brites, and F. Pereira, “Motion compensated refinement for low complexity pixel based distributed video coding,” Proc. of IEEE Int''l Conf. on Advanced Video and Signal-Based Surveillance, Como, Italy, Sep. 2005.
[14] S. Klomp, Y. Vatis, J. Ostermann, “Side information interpolation with sub-pel motion compensation for Wyner-Ziv decoder,” Int’l Conf. on Signal Processing and Multimedia Applications (SIGMAP), Setúbal, Portugal, August 7-10, 2006.
[15] A. Aaron, S. Rane, and B. Girod, “Wyner-Ziv video coding with hash-based motion compensation at the receiver,” Proc. of IEEE Int’l Conf. on Image Processing (ICIP), Singapore, Oct. 2004.
[16] R. Puri and K. Ramchandran, “PRISM: a new robust video coding architecture based on distributed compression principles,” Allerton Conf. on Communication, Control, and Computing, Allerton, IL, 2002.
[17] R. Puri and K. Ramchandran, “PRISM: an uplink-friendly multimedia coding paradigm,” Proc. of IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Hong Kong, China, April 2003.
[18] R. Puri and K. Ramchandran, “PRISM: a “reversed” multimedia coding paradigm,” Proc. of IEEE Int’l Conf. on Image Processing (ICIP), Barcelona, Spain, September 2003.
[20] E. Martinian, A. Vetro, J. Ascenso, A. Khisti, and D. Malioutov, “Hybrid distributed video coding using SCA codes,” Proc. of Int’l Workshop on Multimedia Signal Processing (MMSP), October 2006.
[21] C. Brites, J. Ascenso, F. Pereira, “Studying temporal correlation noise modeling for pixel based Wyner-Ziv video coding,” Proc. of IEEE Int’l Conf. on Image Processing (ICIP), Atlanta, USA, October 8-11, 2006.
[22] R. P. Westerlaken, S. Borchert, R. K. Gunnewiek, R. L. Lagendijk, “Dependency channel modeling for a LDPC-based Wyner-Ziv video compression scheme,” Proc. of IEEE Int’l Conf. on Image Processing (ICIP), Atlanta, USA, October 2006.
[23] W. E. Ryan, “An Introduction to LDPC Codes,” CRC Handbook for Coding and Signal Processing for Recording Systems, CRC Press, 2004.
[24] Z. Li, L. Liu, E. J. Delp, “Wyner-Ziv video coding with universal prediction,” IEEE Trans. on Circuits and Systems for Video Technology, vol. 16, no. 11, pp. 1430-1436, November 2006.
[25] A. Aaron, E. Setton, and B. Girod, “Towards Practical Wyner-Ziv Coding of Video,” Proc. of IEEE Int’l Conf. on Image Processing (ICIP), Barcelona, Spain, Sept. 2003.
[26] J. Ascenso, C. Brites, F. Pereira, “Content adaptive Wyner-Ziv video coding driven by motion activity,” Proc. of IEEE Int’l Conf. on Image Processing (ICIP), Atlanta, USA, October 8-11, 2006.
[27] M. Tagliasacchi, A. Trapanese, S. Tubaro, J. Ascenso, C. Brites, F. Pereira, “Intra Mode Decision Based On Spatio-Temporal Cues In Pixel Domain Wyner-Ziv Video Coding,” Proc. of IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Toulouse, France, May 2006.
[28] D. Varodayan, A. Aaron and B. Girod, “Rate-adaptive codes for distributed source coding,” EURASIP Signal Processing Journal, Special Section on Distributed Source Coding, vol. 86, no. 11, pp. 3123-3130, November 2006.
[29] C. Brites, J. Ascenso, F. Pereira, “Studying Temporal Correlation Noise Modeling For Pixel Based Wyner-Ziv Video Coding,” Proc. of IEEE Int’l Conf. on Image Processing (ICIP), Atlanta, USA, October 8-11, 2006.
[30] M. Dalai, R. Leonardi, F. Pereira, “Improving Turbo Codec Integration In Pixel-Domain Distributed Video Coding,” Proc. of IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Toulouse, France, May 14-19, 2006.
[31] Wei-Jung Chien, Lina J. Karam, Glen P. Abousleman, “Distributed video coding with lossy side information,” Proc. of IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Toulouse, France, May 2006.
[32] Dung-Chan Tsai, Chang-Ming Lee, Wen-Nung Lie, “Dynamic key block decision with spatio-temporal analysis for Wyner-Ziv video coding,” Proc. of IEEE Int’l Conf. on Image Processing (ICIP), San Antonio, TX, September 2007.