改進多視角視訊編解碼架構下之分散式視訊編碼器效能

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研究生：	李世杰 Shih-Chieh Lee
論文名稱：	改進多視角視訊編解碼架構下之分散式視訊編碼器效能 On Improving Distributed Video Codec Performance Under Multiview Video Codec Framework
指導教授：	陳建中 Jiann-Jone Chen
口試委員:	杭學鳴 Hsueh-Ming Hang 陳永昌 Yung-Chang Chen 黃文吉 Wen-Jyi Hwang 楊士萱 Shih-Hsuan Yang 蘇柏齊 Po-Chyi Su 蘇順豐 Shun-Feng Su
學位類別：	博士 Doctor
系所名稱：	電資學院 - 電機工程系 Department of Electrical Engineering
論文出版年：	2013
畢業學年度：	101
語文別：	英文
論文頁數：	119
中文關鍵詞：	分散式視訊編碼、多描述編碼、多視角視訊編碼
外文關鍵詞：	multiple description coding, central decoder control
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本論文探討如何應用分散式視訊編碼方法(Distributed Video Coding, DVC)針對視訊影像間的關聯性編碼，並應用通道編碼將編碼運算複雜度有效的轉移到解碼端，同時在解碼端透過中央聯合解碼重建原始視訊影像；本論文所提出的編碼控制方法經由模擬實際的通道傳輸環境來驗證結果。全文含二個子研究項目，分別討論分散式編碼器在單一及多視角視訊編碼上的應用: (1)結合DVC和多描述編碼系統(Multiple Description Coding, MDC)，在模擬真實的傳輸環境下降低雜訊的干擾，並且利用集中式解碼器選擇較佳的影像輸出; (2)針對DVC應用在多視角視訊編碼(Multiview Video Coding, MVC)的架構下，提出一個能提升輔助資訊精確度的處理方法，從而改善重建影像品質。
因DVC可以將編碼運算的複雜度轉移到解碼器，故可廣泛應用在需要佈署低複雜度之視訊擷取裝置系統:如有線或無線的感知監測網路。本論文第一部份討論如何改善DVC的效能和其相關的應用，並依據訊號的特性討論DVC系統中組成的功能單元對於輔助資訊(Side information SI)和重建影像品質的影響。將DVC應用於MDC的架構簡稱為MD-DVC，我們提出改善MDC之中央解碼器(Central Decoder)最佳影像輸出選擇機制以降低雜訊在影像傳輸中的干擾。
第二部份討論分散式編碼器在多視角影像傳輸架構下的應用，稱為多視角分散式視訊編碼(Multiview Distributed Video Coding, MV-DVC)，控制目的是減少龐大資料的傳輸。在MV-DVC解碼端，我們提出結合影像區塊分類和動量估測權重分配(Categorized blOck Matching Prediction with fidelity wEights, COMPETE)以重建出可信度較高的輔助資訊(Confidence SI)。本文所提出的COMPETE方法充分運用週圍相鄰影像的關聯性，對等待重建的區塊進行分類，並且運用基於尺度不變轉換、區塊比對之動量估測和權重分配的法則，在不增加計算複雜度的條件下，有效提高SI Confidence，並改善了重建畫面的品質。在解碼端，根據轉換域係數分佈的特性，我們設計了一個適用於渦輪解碼器的優先權控制演算法，在模擬結果證實此法可減少用於修正的同位檢查位元的傳輸量，並降低渦輪解碼器迭代解碼的時間。

In a distributed video coder (DVC), it encodes multiple correlated images and utilizes error correction code to shift the encoding complexity to the decoder, in which a central decoder performs joint decoding to reconstruct the video frames. For the first part of this thesis, how to improve the DVC performances and its extended applications were investigated. By shifting the encoding complexity to the decoder, the DVC can be utilized in wireless/wired sensors or surveillance networks that demands lower-complexity capturing devices. The signal processing targets of all the DVC function units were investigated to justify the performance of SI and Wyner-Ziv frame reconstruction. The multiple description coding (MDC), that decomposes one single media into several descriptions and transmits them through different channels, can combat noises. Each MDC description contributes to improve the reconstructed media quality when decoded. For robust transmission, the DVC is integrated with a multiple description coder (MDC), abbreviated as MD-DVC. For the MD-DVC, we proposed to improve the central decoder to combat transmission errors. We also proposed to improve the side information (SI) confidence by a Categorized blOck Matching Prediciton with fidEliTy wEight (COMPETE) method, by which better DVC reconstructed images can be obtained. In addition, the video signal properties were utilized to improve the rate control procedure, which would reduce the number of requested parity bits. The MD-DVC control methods help to provide a stable codec platform for mobile encoders. At the side encoder, a DVC-based adaptive differential pulse code modulation (DPCM) method was proposed to utilize inter-frame correlation to enhance rate-distortion performances. For the MD-DVC central decoding, intra- and inter-description correlations were exploited and utilized to dynamically select the best reconstructed frames among all the descriptions, instead of selecting just one description or all key-frames from two descriptions. For the thesis second part, the multi-view video codec (MVC) embedded with the DVC was investigated. In the COMPETE, blocks were categorized for different coding procedures and prediction by fidelity weights was proposed to yield high confidence SI. The transform coefficient properties, i.e., DCs and ACs, were exploited to design the priority rate control for the turbo coder, such that the DVC decoding can be carried out with the minimum number of parity bits. Experiments justified that the proposed COMPETE with the rate control can be carried out with lower time complexity, while yielding better reconstructed video quality.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1
1 The Conventional Video Codec . .  . . . . . . . . . . . . . . . . . . . . 2
1.1 The H.264/AVC Video Coding .. . . . . . . . . . . . . . . . . . . . . . 3
1.2 H.264/AVC Intra-frame Prediction . . . . .. . . . . . . . . . . . . . . 3
1.3 H.264/AVC Inter-frame Prediction . . . . .. . . . . . . . . . . . . . . 4
1.4 Transform, Quantization and Entropy Coding . . . . . . .. . . . . . . . 4
2 The Recent Video Codec .. . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1 Information Theory Background of DVC  . . . . . . . . . . . . . . . . . 5
2.2 The Multiple Description Video Coding . . . . . . . . . . . . . . . . . 6
2.3 The Multi-view Video Coding . . . . . . . . . . . . . . . . . . . . . . 7
3 Organization and Contributions of the Thesis  . . . . . . . . . . . . . . 8
Distributed Video Coding . . . . . . . . . . . . . . . . . . . . . . . . . 10
1 Quantization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2 The RCPT Channel Codec . . . . . . . . . . . . . . . . . . . . . . . . . 12
3 Side Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
4 Wyner-Ziv Decoder . . . . . . . . . . . . . . . . . . . . . . . . . . .  14
5 Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
The Multiple Description Video Codec with Adaptive Residual
Distributed Coding . . . . . . . . . . . . . . . . . . . .. . . . . . . . . .18
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2 MD-DVC system . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  20
3 MD-DVC-RT System . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3.1 Wyner-Ziv Residual Coding . . . .. . . . . . . . . . . . . . . . . . . 24
3.2 Image Prediction of MD-DVC-RT . . . . .. . . . . . . . . . . . . . . . 27
4 Central Decoder Control . . . . . . . . . . . . . . . . . . . . . . . .  30
5 MD-DVC Error Distribution Analysis . . . . . . . . . . . . . . . . . . . 32
6 Simulation Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
6.1 PSNR of Lossless Transmission Dc( ˜ S1 = S1, ˜ S2 = S2) . . .. . . . . 36
6.2 PSNR of Single Description Dc( ˜ S1 = S1, ˜ S2 = 0) . .. . . . . . . . 37
6.3 Transmission over Wireless Fading Channel ( ˜ Si 6= Si) . . . .. . . . 43
6.4 Central Decoder Control . . .. . . . . . . . . . . . . . . . . . . . . 46
6.5 Practical Implementation . . . . . . . . . . . . . . . . . . . . . . . 51
6.6 Complexity Analysis . . .. . . . . . . . . . . . . . . . . . . . . . . 51
7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  53
The Distributed Video Coder under a Multi-view Video Codec
Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .54
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
2 MV-DVC Side Information .. . . . . . . . . . . . . . . . . . . . . . . . 59
2.1 Side Information Reconstruction . . . .. . . . . . . . . . . . . . . . 59
2.2 COMPETE Side Information . . . . . . . . . . . . . . . . . . . . . . . 62
2.2.1 Homography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
2.2.2 Scale Invariant Frame Transform . . . . . . . . .. . . . . . . . . . 63
2.2.3 Interpolation and Homography . . . . . . . . . . . . . . . . . . . . 64
2.3 Block Matching Prediction . . .. . . . . . . . . . . . . . . . . . . . 66
3 The MV-DVC Rate Control Algorithm . . .. . . . . . . . . . . . . . . . . 71
3.1 Wyner-Ziv Coding . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.2 Rate Control Mechanism . . . . . . . . . . . . . . . . . . . . . . . . 76
4 Simulation Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.1 Performance Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.1.1 Error Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.1.2 SI Confidence . . . . . .. . . . . . . . . . . . . . . . . . . . . . 84
4.1.3 Objective Performance Evaluation . . . . . . . . . . . . . . . . . . 86
4.2 Time Complexity Analysis . . . . . . . . . . . . . . . . . . . . . . . 92
4.2.1 MCTI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
4.2.2 Fusion-based Homography . . . . . . . . .. . . . . . . . . . . . . . 93
4.2.3 H-MVME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93
4.2.4 COMPETE . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . 94
4.2.5 Practical Execution Time Evaluation . . . . . . . . .. . . . . . . . 95
4.3 Subjective Performance Evaluation . . . .. . . . . . . . . . . . . . . 95
4.3.1 Reconstructed SI frames . . . . . . .. . . . . . . . . . . . . . . . 95
4.3.2 Reconstructed WZ images . . . . . . . .. . . . . . . . . . . . . . . 96
4.4 Practical Applications . . . . . . . . . . . . . . . . . . . . . . . . 97
5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  99
Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
1 Contribution of the Thesis . . . . . . . . . . . . . . . . . . . . . .  100
2 Future Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .103
Appendix A Optimal Bit Allocation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
Appendix B Turbo Coder Performance .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .113
Appendix C MDVC Performance on CIF videos . . . . . . . . . . . . . . . . . 115

                                

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