基於支持向量機之HEVC低運算複雜度畫面內預測演算法研究

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姓名

黃上恩(Shang-en Huang) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

基於支持向量機之HEVC低運算複雜度畫面內預測演算法研究
(Low Computational Complexity Algorithm for HEVC Intra Prediction with Support Vector Machine)

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摘要(中)

最新視訊編碼標準為高效率視訊編碼(High Efficiency Video Coding, HEVC)，HEVC比起先前的視訊編碼標準H.264/AVC編碼效率更佳。HEVC的編碼單元(Coding Unit , CU)採用了四分樹(Quad-Tree)的編碼架構增加其編碼效能，在畫面內預測中，為了使預測更精準，使用了35個模式來進行預測，同時也大幅的增加其編碼的複雜度。因此本篇論文提出一個應用於畫面內編碼的CU深度快速決策演算法，擷取三種原始畫面的資訊以及空間上的相關性做為特徵(Feature)，其中包含了變異數、低頻交流值以及鄰近編碼單元的深度資訊，依照輸入特徵給予支持向量機(Support vector machine, SVM)所預測出的結果，判斷當前CU是否往下進行切割；於畫面內預測中，則是使用索爾運算子(Sobel)來判斷當前畫面預測單元(Prediction Unit,PU)的主要方向以及鄰近幾個方向做為我們約略模式決策(Rough Mode Decision, RMD)的候選模式，而且我們也減少了RDO(Rate-Distortion Optimization)的候選模式個數以達到減省時間的效果。由實驗結果可知，我們所提出的演算法在維持一定影像品質之下，平均能夠節省48.3%的整體編碼時間。

摘要(英)

High efficiency video coding (HEVC) is the state-of-the-art video coding standard. HEVC is better than the previous video coding standard H.264/AVC on the coding efficient. The coding unit(CU) of HEVC uses a Quadtree-based coding structure to increase coding performance. In order to predict more accurately, using 35 prediction modes in intra prediction. Simultaneously, it also increases its coding complexity. Hence, in this thesis, we proposed an SVM based fast intra CU depth decision algorithm is proposed to reduce the computational complexity. It is convenient to develop the criterion of early CU splitting and termination by applying SVM with features extracted from spatial domain, frequency domain, including Variance, low-frequency AC value, and neighboring CU depth. After extracting the features, SVM predict the current CU will be split or be terminated. In intra prediction, we use sobel operator to distinguish the direction of PU(Prediction Unit) and the neighbor mode to be the candidates of rough mode decision and we also reduce the candidates of rate-distortion optimization. The experimental results show that our proposed algorithm achieves 48.3% encoding time saving on average without significant degradation of coding performance.

關鍵字(中)

★ HEVC
★ 編碼單元
★ 畫面內預測
★ 支持向量機

關鍵字(英)

★ HEVC
★ Coding Unit
★ Intra Prediction
★ SVM

論文目次

章節目錄
第一章緒論 1
1.1 高效率視訊編碼(HEVC)簡介 1
1.2 研究動機與目的 2
1.3 論文架構 7
第二章畫面內編碼預測模式介紹與文獻探討 12
2.1 HEVC畫面內編碼預測介紹 12
2.2 編碼單元及預測模式決策演算法相關文獻回顧 20
第三章支持向量機應用於HEVC編碼單位(CU)之快速演算法 24
3.1支持向量機介紹(Support Vector Machine) 24
3.2特徵選取 26
3.2.1變異數(Variance) 26
3.2.2 低頻交流值(AC_low) 29
3.2.3 鄰近CU深度值資訊(Neighboring CU) 33
3.3基於支持向量機之快速編碼單元深度決策演算法 36
3.3.1支持向量機之快速編碼單元深度決策演算法 36
3.3.2綜合效能分析 38

第四章快速畫面內預測模式決策演算法之研究與探討 69
4.1快速畫面內預測模式決策演算法相關文獻回顧 69
4.2改良型降取樣梯度邊界特徵之快速畫面內模式決策演算法 79
4.2.1降取樣梯度特徵邊界演算法之探討與改良 79
4.2.2效能分析 83
4.2.3合併畫面內預測編碼單元深度及模式之效能分析 92
4.3改良型快速畫面內模式決策演算法 101
4.3.1畫面內模式決策演算法之探討與改良 101
4.3.2合併畫面內預測編碼單元深度及模式之效能分析 105
第五章結論與未來展望 126
參考文獻 127

參考文獻

參考文獻
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指導教授

林銀議(Yin-yi Lin)

審核日期

2015-7-30

推文