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研究生： 陳慶樺
Ching-hua Chen
論文名稱： 整合多視角與分散式視訊編碼之改良式區塊比對預測演算法
An improved block matching and prediction algorithm for multi-view video with distributed video coder
指導教授： 陳建中
Jiann-jone, Chen
口試委員: 林大衛
none
郭天穎
none
劉俊麟
none
鍾國亮
none
學位類別： 碩士
Master
系所名稱： 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年： 2010
畢業學年度： 98
語文別： 中文
論文頁數： 75
中文關鍵詞： 多視角分散式視訊編碼 、區塊比對預測 、打洞式渦輪碼
外文關鍵詞： multi-view distributed video coding, block matching and prediction, RCPT
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    • 隨著視訊技術不斷地進步，多媒體服務平台逐漸能夠提供使用者搭配偏光眼鏡或不需配帶眼鏡即可觀看三維電視(Three-dimensional Television, 3D TV)呈現立體場景的效果，將不同視角畫面的關聯性做有效的多視角視訊編碼(Multi-view Video Coding, MVC)，然而該架構並不適用於行動通信裝置與無線感知監測網路的應用，因而使用分散式視訊編碼(Distributed Video Coding, DVC)技術來處理多視角視訊影像傳輸的問題，將編碼端的複雜度轉移至解碼端，稱為多視角分散式視訊編碼(Multi-view Distributed Video Coding, MDVC)。本論文提出改進MDVC架構的方法：(1)在解碼端提出利用轉換域係數分佈的特性，設計優先權速率控制的渦輪解碼器。(2)提出一個基於尺度特徵不變轉換(Scale Invariant Feature Transform, SIFT)的區塊比對預測(Block Matching and Prediction, BMP)演算法，簡稱為SIFT-BMP，產生更精確的輔助資訊(Side Information, SI)影像，提供DVC重建較佳的影像品質。與文獻中的方法相比，本論文所提的方法能提供較低的運算複雜度與時間消耗，並得到較佳的重建視訊品質。實驗結果顯示提出的SIFT-BMP方法相較於混合型的多視角運動估計(Hybrid Multi-view Motion Estimation, H-MVME)方法可降低運算量1.29~2.56倍，而解碼的PSNR效能與H.264/AVC畫面內(intra)編碼模式相比，提升平均PSNR約0.9至3dB。

    With the advance of video coding technology, the multimedia platform can provide Three-dimensional Television (3D TV) display for users with or without glasses. The inter-view video correlation has been exploited to perform efficient multi-view video coding. For the extension applications on mobile devices and wireless networks, the distributed video codec (DVC) can be utilized to shift encoder complexity to decoder under the multi-view video coding framework, denoted as Multi-view Distributed Video Coding (MDVC). Several coding control methods have been proposed to improve the MDVC codec performance: (1) The block transform coefficients are utilized to design the priority rate control for the turbo coder at decoder. (2) A Block Matching and Prediction algorithm, based on Scale Invariant Feature Transform, abbreviated as SIFT-BMP, has been proposed to yield more accurate side information for better DVC reconstructed images. In comparisons with other view estimation method, the proposed method can provide lower computational complexity and time consumption, while yielding better reconstructed video quality. Simulations show that the proposed SIFT-BMP method can reduce the time complexity of motion estimation to 1.29~2.56 times smaller, as compared to previous Hybrid Multi-View Motion Estimation (H-MVME) methods, while the PSNR of decoded video can be improved 0.9~3dB, as compared to H.264/AVC intra coding.

    摘要 I Abstract II 誌謝 III 目錄 IV 圖目錄 VI 表目錄 IX 第一章 緒論 1 1.1 研究動機與目的 1 1.2 問題描述 2 1.3 研究方法 3 1.4 論文組織 5 第二章 背景知識與相關研究 6 2.1 分散式視訊編碼之多視角視訊編碼 6 2.1.1 多視角視訊編碼源起 6 2.1.2 分散式視訊編碼理論 7 2.1.3 整合分散式視訊編碼與多視角視訊編碼架構 9 2.2 多視角輔助資訊重建 10 2.2.1 運動補償時間域內插 10 2.2.2 透視轉換模型 11 2.2.3 多視角運動估計 13 2.3 相關模擬工具 14 2.3.1 H.264視訊編碼器 14 2.3.2 RCPT之渦輪編碼器 17 2.3.3 SIFT之特徵比對法 19 第三章 分散式架構下改良之多視角視訊編碼系統 23 3.1 MDVC系統 23 3.2 速率控制演算法 30 3.3 輔助資訊重建之區塊比對演算法 35 3.4 輔助資訊重建之複雜度分析 40 第四章 模擬結果與比較 43 4.1 實驗參數設定 43 4.2 實驗數據比較 45 4.2.1 重建輔助資訊影像之品質 46 4.2.2 重建輔助資訊影像與編解碼之時間複雜度 49 4.2.3 解碼影像之PSNR編碼效能 51 4.3 實驗結果展示 59 4.3.1 重建輔助資訊影像 59 4.3.2 解碼之WZ影像 65 第五章 結論與未來展望 71 5.1 結論 71 5.2 未來展望 72 參考文獻 73

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