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研究生: 張文聖
Wen-Sheng Chang
論文名稱: 利用圖場的動作補償內插方法之分散式視訊編碼
Distributed Video Coding Using Field Motion-Compensated Interpolation Method
指導教授: 陳永昌
Yung-Chang Chen
陳志明
Chih-Ming Chen
口試委員:
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年: 2007
畢業學年度: 95
語文別: 英文
論文頁數: 42
中文關鍵詞: 分散式附帶資訊場內圖場場間圖場解交錯
外文關鍵詞: Wyner-Ziv, side information, intra-field, inter-field, de-interlacing
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  • 傳統的視訊編碼通常是在編碼端利用複雜的預測迴圈,去找出資料的統計相關性,進而達到壓縮的效果。不同於此的是,分散式視訊編碼 (Distributed Video Coding) 提供了另一種有效率的壓縮方式。在分散式視訊編碼當中,資料的統計相關性被利用在解碼端,因此讓編碼端變得較簡單,所以非常適合需要節省編碼端的電力和複雜度的應用,例如無線視訊電話,或無線監視系統等等。Wyner-Ziv視訊編碼是分散式視訊編碼的一個特殊情況,它將視訊的圖框獨立且帶有失真地編碼,再利用鄰近圖框作為附帶資訊(side information)來共同解碼。因為碼率-失真的表現跟附帶資訊的可信度有高度的相關,我們主要的目標就是如何完善地利用資料的統計特性來製造出更可靠的附帶資訊。
    在這篇論文中,我們提出了一個改進過的Wyner-Ziv視訊編碼方法,藉由圖場動作補償的內插方法實現。也就是一個「場內圖場編碼-場間圖場解碼」的系統。我們將一張圖框分離成一個Wyner-Ziv圖場及一個關鍵圖場(key field)。接著我們可以在解碼端利用鄰近的圖場來內插出Wyner-Ziv圖場的附帶資訊。我們使用了一個解交錯的演算法,使得各個圖場之間不僅是時間上而且空間上的資料的相關性都會在解碼端被利用。透過這個方法,我們能夠得到一個較好的附帶資訊。另外,編碼端仍然維持簡單而且不用傳送額外的資訊或記憶體空間。這個方法提供了比一般的Wyner-Ziv視訊編碼方法有更好的碼率-失真表現。


    Different from conventional video coding, which usually employs sophisticated prediction loop to exploit the statistics at the encoder, distributed video coding (DVC) provides another way to perform efficient compression. In DVC, the statistics are exploited at the decoder to make the encoder simpler and thus it is well-suited for applications where the power and complexity are scarce sources at the encoder, e.g., wireless video phone. Wyner-Ziv video coding is a particular case of DVC that it encodes a frame independently with lossy coding, but decodes them jointly by using adjacent frame as side information. Since the rate-distortion performance is highly related to the faithfulness of the side information, the major task is how to utilize the statistics of the correlated source and generate the side information more reliably.
    In this thesis we propose a modified Wyner-Ziv video coding solution, using field motion-compensated interpolation method. That is, an “intra-field encoding and inter-field decoding” system. We separate each frame into one Wyner-Ziv field and one key field. Then we can use adjacent fields to interpolate the side information of each Wyner-Ziv field at the decoder. Hence a de-interlacing algorithm is employed at the decoder to exploit not only temporal but also spatial similarities between adjacent fields. By using this method, we may produce more accurate side information. Besides, the encoder can still be simple and no extra information (e.g., hash codewords) is sent from the encoder to the decoder or extra memory space at the encoder. This allows better rate-distortion performance compared to conventional Wyner-Ziv video coding scheme.

    Table of Contents i Chapter1 Introduction 1 1.1 Theoretical Backgroun 2 1.1.1 Slepina-Wolf Theorem 2 1.1.2 Wyner-Ziv Theorem 3 1.2 Wyner-Ziv Video Coding 3 1.3 Applications 4 1.4 Main Contribution of this Thesis 5 1.5 Thesis Organization 5 Chapter2 Overview of Related Work 6 2.1 Stanford Wyner-Ziv Video Coding Solution 6 2.1.1 Quantization and turbo encoding 7 2.1.2 Side information interpolation 8 2.1.2 Virtual channel statistics model and reconstruction 8 2.2 Other Wyner-Ziv Video Coding Improvement 9 2.3 The Main Challenge 10 Chapter3 WZ Video Coding Using Field De-interlacing Method 11 3.1 Intra-field Encoder 12 3.1.1 Field Separation 12 3.1.2 Quantization 13 3.1.3 Turbo Encoder 14 3.2 Inter-field Decoder 15 3.2.1 Adaptive Motion-Compensated Side Information Interpolation by De-interlacing Algorithm 16 3.2.2 Turbo Decoder 26 3.2.3 Reconstruction 28 3.2.4 Field Combination 29 Chapter4 Simulation Result 30 4.1 Simulation Environment 30 4.2 Simulation Result 32 4.2.1 Foreman sequence 32 4.2.2 Mother and daghter sequence 36 Chapter5 Conclusions and Future Works 39 5.1 Conclustions 39 5.2 Future Works 40 References 41

    [1] Slepian J. D. and Wolf J. K, “Noiseless Coding of Correlated Information Sources,” IEEE Trans. Information Theory, vol. IT-19, pp. 471-480, Jul. 1973.

    [2] Wyner A. D. and Ziv J. “The Rate-Distortion Function for Source Coding with Side Information at the Decoder,” IEEE Trans. Information Theory, vol. 22, no. 1, pp. 1-10, Jan. 1976.

    [3] A. Aron, R. Zhang and B. Girod, “Wyner-Ziv Coding of Motion Video,” Proceedings of Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, USA, November 2002.

    [4] R. Puri and K. Ramchandran, “PRISM: A New Robust Video Coding Architecture Based on Distributed Compression principles,” Proceedings of 40th Allerton Conference on Communication, Control and Computing, Allerton, Illinois, USA, October 2002.

    [5] A. Aaron, S .Rane, E. Setton and B. Girod, “Transform-Domain Wyner-Ziv Codec for Video,” Proceedings of SPIE Visual Communications and Image Processing Conference San Jose, California, USA, January 2004.

    [6] B. Girod, A. M. Aaron, S. Rane, and D. Rebollo-Monedero, “Distributed Video Coding,” Proceedings of the IEEE, vol. 93, no. 1, pp.71-83 Jan. 2005.

    [7] 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, Image Processing, Multimedia Communications and Services, Smolenice, Slovak Republic, July 2005.

    [8] C. Brites, J. Ascenso, and F. Pereira, “Improving Transform Domain Wyner-Ziv Video Coding Performance,” Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, Toulouse, May 2006.

    [9] D. Rowitch and L. Milstein, “On the Performance of Hybrid FEC/ARQ Systems using Rate Compatible Punctured Turbo Codes,” IEEE Transactions on Communications, vol. 48, no.6, pp.948-959, June 2000.
    [10] A. Aaron, S. Rane and B. Girod, “Wyner-Ziv Video coding with Hash-Based Motion Compensation at the Receiver,” Proceedings of IEEE International Conference on Image Processing, Vol. 5, pp. 3097-3100, Singapore, October 2004.

    [11] A. Aaron and B. Girod, “Wyner-Ziv Video Coding with Low Encoder Complexity,” Proceedings. Of Picture Coding Symposium, San Francisco, CA, USA, December 2004.

    [12] B. Vucetic and J. Yuan, “Turbo Codes Principles and Applications,” Kluwer Academic Publishers, 2000.

    [13] Ming-Chieh Hsi, “An Implementation of Adaptive Motion-Compensated Interpolation for De-interlacing System,” M.S Thesis, Department of Electronic Engineering, NTHU, 2004.

    [14] A. Viterbi, “An Intuitive Justification and a Simplified Implementation of the MAP Decoder for Convolutional Codes,” IEEE JSAC, pp. 260-264, Feb. 1998.

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