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研究生： 林泂良
Lin, Jiung-Liang
論文名稱： 錯誤容忍技術運用於可調式編碼之研究
Error Resilient Techniques for Scalable Video Coding
指導教授： 郭致宏
Kuo, Chih-Hung
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： 2010
畢業學年度： 98
語文別： 英文
論文頁數： 91
中文關鍵詞： 可調式編碼 、累贅編碼 、全畫面修復 、錯誤容忍 、多核心
外文關鍵詞： SVC, Redundant coding, Frame based, Error resilience, Multi-core
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    • 在本論文中，我們提出重複宏塊邊緣搜尋演算法來增加錯誤修復的影像品質。相較於邊緣搜尋演算法，重複宏塊邊緣搜尋法修正其不適合做完整畫面修復的缺點，在編碼時，我們將較為重要的宏塊做重複編碼，因此當一個畫面無法解碼時，較為重要的宏塊可以先做解碼，並且提供周圍宏塊搜尋時定位的資訊，藉此大幅增加修正畫面的可靠度。在文中，我們將探討重複宏塊編碼數量以及解碼排序對影像畫面修復的影響。相較於傳統動量內插演算法，我們提出的方法在封包遺失率為10%時，優於傳統演算法至少3dB。另外，我們討論其他方式運用在演算法中的影響，包括在搜尋時增加邊緣連續的條件、搜尋時以動量內插做搜尋中心以減少計算複雜度、單方向/雙方向預測、平行處理用運在雙核心的機制等等。

    In this thesis, a redundant macro block coding with texture-based selective boundary matching algorithm (RMB-TSBMA) is introduced to improve the video quality for error recovery. Different from texture-based selective boundary matching algorithm (TSBMA), the algorithm is more suitable for frame based recovery. The RMB coding encodes the information of some essential blocks. When a frame gets lost, we can first decode RMBs, and then neighboring MBs with TSBMA, so that the RMBs can provide the correct position for boundary MBs matching to get better visual quality. The influences of the RMB number and the reordering method are also discussed. Compared with the other algorithms, the PSNR of the proposed RMB-TSBMA performs better than conventional method of temporal direct mode (TDM) by over 3dB at the packet loss rate 10%. Besides, we talk about the other topic for RMB-TSBMA, including considering the edges when searching in the algorithm, setting search center as the MVs of TDM to decrease the search window, single-direction/bi-direction prediction for boundary search, and parallel execution for dual-core process.

    論文口試委員審定書 . . . . . . . . . . . . . . . . . . . . . i 摘要. . . . . . . . . . . . . . . . . . . . . . . . . . . ii Abstract . . . . . . . . . . . . . . . . . . . . . . . . iii 誌謝. . . . . . . . . . . . . . . . . . . . . . . . . . . iv Contents . . . . . . . . . . . . . . . . . . . . . . . . . v List of Tables. . . . . . . . . . . . . . . . . . . . . . ix List of Figures. . . . . . . . . . . . . . . . . . . . . . x 1 Introduction . . . . . . . . . . . . . . . . . . . . . . 1 1.1 Background and Motivation . . . . . . . . . . . . . . 1 1.2 Contributions . . . . . . . . . . . . . . . . . . . . 2 1.3 Organization of Thesis. . . . . . . . . . . . . . . . 3 2 Research Background. . . . . . . . . . . . . . . . . . . 4 2.1 Overview of SVC . . . . . . . . . . . . . . . . . . . 4 2.1.1 SVC Codec. . . . . . . . . . . . . . . . . . . . . 5 2.1.2 Hierarchical B Frame . . . . . . . . . . . . . . . 6 2.1.3 Temporal Scalability . . . . . . . . . . . . . . . 7 2.1.4 Spatial Scalability. . . . . . . . . . . . . . . . 8 2.1.5 SNR Scalability. . . . . . . . . . . . . . . . . . 9 2.1.6 Error Recovery. . . . . . . . . . . . . . . . . . 10 2.2 Error Concealment. . . . . . . . . . . . . . . . . . 10 2.2.1 Frame Copy (FC) . . . . . . . . . . . . . . . . . 11 2.2.2 Motion Vectors Copy (MVC) . . . . . . . . . . . . 11 2.2.3 Motion and Residual Upsampling (BLSkip) . . . . . 12 2.2.4 Temporal Direct Mode (TDM). . . . . . . . . . . . 12 2.3 Error Resilience . . . . . . . . . . . . . . . . . . 13 2.3.1 Reversible Length Coder (RVLC). . . . . . . . . . 14 2.3.2 Gradual Decoding Refresh (GDR). . . . . . . . . . 14 2.3.3 Residual Motion-Vector (RMV). . . . . . . . . . . 16 2.3.4 Flexible Macro-block Ordering (FMO) . . . . . . . 16 3 RMB-TSBMA . . . . . . . . . . . . . . . . . . . . . . . 19 3.1 Encoding Procedure . . . . . . . . . . . . . . . . . 19 3.1.1 Sobel Detector. . . . . . . . . . . . . . . . . . 20 3.1.2 Sorting and Choosing RMBs . . . . . . . . . . . . 24 3.1.3 Redundant Macro-block Coding. . . . . . . . . . . 27 3.2 Decoding Procedure . . . . . . . . . . . . . . . . . 30 3.2.1 Reordering. . . . . . . . . . . . . . . . . . . . 31 3.2.2 Boundary Matching Algorithm . . . . . . . . . . . 33 3.2.3 Texture-based Selective Boundary Matching Algorithm . . . . . 34 3.3 Recovery Strategy. . . . . . . . . . . . . . . . . . 35 4 Implementation Issues of RMB-TSBMA. . . . . . . . . . . 38 4.1 RMB-TSBMA with Other Conditions. . . . . . . . . . . 38 4.1.1 RMB-TSBMA with Edge . . . . . . . . . . . . . . . 38 4.1.2 RMB-TSBMA with TDM. . . . . . . . . . . . . . . . 39 4.2 Single-direction/Bi-direction Prediction . . . . . . 40 4.2.1 Bi-direction Prediction . . . . . . . . . . . . . 42 4.2.2 Single-direction Prediction . . . . . . . . . . . 42 4.3 Considering Loss of RMBs . . . . . . . . . . . . . . 44 4.4 RMB-TSBMA on Dual-Core Architecture. . . . . . . . . 45 4.4.1 Choosing RMBs . . . . . . . . . . . . . . . . . . 46 4.4.2 Reordering. . . . . . . . . . . . . . . . . . . . 47 4.4.3 Analysis. . . . . . . . . . . . . . . . . . . . . 49 5 Experimental Results. . . . . . . . . . . . . . . . . . 55 5.1 Simmulation Settings . . . . . . . . . . . . . . . . 55 5.2 Simulation Results . . . . . . . . . . . . . . . . . 57 5.2.1 RMB-TSBMA . . . . . . . . . . . . . . . . . . . . 57 5.2.2 RMB-TSBMA with Other Conditions . . . . . . . . . 60 5.2.3 Single-direction/Bi-direction Prediction. . . . . 61 5.2.4 Considering Loss of RMBs. . . . . . . . . . . . . 61 5.2.5 Dual-core Implementations . . . . . . . . . . . . 61 6 Conclusion. . . . . . . . . . . . . . . . . . . . . . . 73 References . . . . . . . . . . . . . . . . . . . . . . . 74 Appendix A. . . . . . . . . . . . . . . . . . . . . . . . 78 Appendix B. . . . . . . . . . . . . . . . . . . . . . . . 80 Appendix C. . . . . . . . . . . . . . . . . . . . . . . . 83 Appendix D. . . . . . . . . . . . . . . . . . . . . . . . 85 Appendix E. . . . . . . . . . . . . . . . . . . . . . . . 90

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