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研究生:李育銘
研究生(外文):Yu-Ming Lee
論文名稱:H.264之快速區塊模式決策演算法之探討
論文名稱(外文):Fast Intermode Decision in H.264/AVC
指導教授:林銀議
指導教授(外文):Yin-Yi Lin
學位類別:碩士
校院名稱:國立中央大學
系所名稱:通訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2006
畢業學年度:94
語文別:中文
論文頁數:64
中文關鍵詞:離散餘弦轉換零區塊偵測H.264 視訊壓縮標準模式決策移動估計區塊模式決策H.264可變區塊大小
外文關鍵詞:H.264variable block sizeintermode decisionDCTmotion estimationmode decisionzero block detection
相關次數:
  • 被引用被引用:2
  • 點閱點閱:203
  • 評分評分:
  • 下載下載:16
  • 收藏至我的研究室書目清單書目收藏:0
新一代的H.264不管是壓縮率和影像品質都明顯優於以往的視訊標準。這是因為其使用了新的技術[1]:可變區塊大小的移動估計(variable block size motion estimation)、多幅參考畫面的移動估計(multi-reference frame motion estimation)、整數轉換(integer transform)。為了達到更好的編碼效益,H.264/AVC更使用位元率失真函數(rate distortion optimization, RDO)技術來得到更好的編碼結果[2]。然而卻使其編碼端的運算複雜度大幅提升,導致增加了硬體實現的困難度;而其計算的複雜度主要分佈在可變區塊大小及多幅參考畫面的移動估計。在此篇論文中,利用時間域的移動緩慢特性(stationary)及空間域的平滑特性(homogenous),我們提出兩種快速區塊模式決策的方法,在影像品質幾乎沒有失真的情況下,降低編碼端的運算複雜度。
The new video coding standard, H.264/AVC, use variable block size ranging from 4x4 to 16x16 and multi-reference frame in interframe coding. This new feature has achieved significant coding gain compared to coding a macroblock using fixed block size. However, this feature results in extremely high computational complexity when brute force rate distortion optimization (RDO) algorithm used. This thesis proposed two fast intermode decision algorithms to decide the best mode in interceding. It make use of the spatial homogenous and the temporal stationary. Based on homogeneity and stationary of the video objects, only a small number of intermodes are selected in RDO process. The experimental results show that the fast intermode decision is able to reduce the encoding time, with a negligible peak-signal-to-noise ratio.
第一章 緒論
1.1 國際視訊壓縮標準簡介 1
1.2 動機與目的 3
1.3 論文架構 5
第二章 H.264 之模式決策與移動估計演算法回顧
2.1 移動估計(motion estimation, ME) 6
2.1.1 可變區塊大小的移動估計 8
2.1.2 非整數點的移動估計 9
2.1.3 多幅參考畫面(multi-frame)的移動估計 9
2.2 H.264 之模式決策與移動估計 11
2.3 快速區塊模式決策演算法 20
2.4 快速移動估計演算法 22
2.5 H.264 之複雜度分析 23
第三章 一種基於變異數之簡單區塊模式決策
3.1 區塊模式決策統計及分析 26
3.2 效能分析 33
3.2.1 環境參數設定 33
3.2.2 不同門檻值之編碼效能比較 34
3.2.3 固定量化參數下之編碼效能比較 36
3.2.4 不同量化參數下之編碼效能比較 38
3.3 簡單區塊模式決策之結論 38
第四章 針對低位元之區塊模式決策
4.1 零區塊(zero block)之介紹及定義 40
4.2 零區塊之統計及分析 43
4.2.1 零區塊之統計 43
4.2.2 零區塊之分析 46
4.3 針對低位元之區塊模式決策流程 49
4.4 效能分析 51
4.4.1 環境參數設定 51
4.4.2 其它快速演算法的簡介 52
4.4.3 固定量化參數下之編碼效能比較 53
4.4.4 不同量化參數下之編碼效能比較 55
4.5 針對低位元率之區塊模式決策的結論 59
第五章 結論和未來展望 60
參考文獻 61
參考文獻

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