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研究生: 林政緯
Lin, Cheng-Wei
論文名稱: 基於動態門檻之H.264/AVC改良區塊動作估測法
Enhanced Block Motion Estimation Based on Dynamic Threshold Schema for H.264/AVC Video Coding
指導教授: 郭淑美
Guo, Shu-Mei
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊工程學系
Department of Computer Science and Information Engineering
論文出版年: 2006
畢業學年度: 94
語文別: 英文
論文頁數: 81
中文關鍵詞: H.264先進數位編碼暴力資料率-失真之最佳化演算法動作估測可變區塊大小
外文關鍵詞: H.264, advanced video coding, rate distortion optimization, variable block size, motion estimation
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  • 在這篇論文裡,基於動態門檻之H.264/AVC 改良區塊動作估測法的方式得到較高的編碼效率。這個方法利用了視訊物件裡的空間和時間特性找到較佳的動態門檻值。根據所提出的方法,一些動作的搜尋能夠較早的結束,並且能夠省下大量的搜尋點。實驗數據顯示了藉著動態門檻機制能夠達到顯著的複雜度下降且編碼損失是可忽略的。

    The dynamic threshold schema-based enhanced block motion estimation for H.264/AVC video coding is proposed in this paper to have a higher coding efficiency. It utilizes spatial and temporal characteristics of video objects to find the better dynamic threshold value. Based on the proposed method, some of the motion searches can be stopped early, and then a large number of search points can be skipped. The experimental results show the significant complexity reduction is achieved with negligible coding loss by dynamic threshold schema.

    Table of Contents Abstract ii Table of Contents iv List of Tables vii List of Figures viii Chapter 1 Introduction 1 Chapter 2 Backgrounds 4 2.1 Overview of H.264/AVC 4 2.1.1 Encoder (forward path) 5 2.1.2 Encoder (reconstruction path) 6 2.2 Inter Prediction 6 2.2.1 Tree Structured Motion Compensation 6 2.2.2 Motion Vectors 8 2.2.2.1 Generating Interpolated Samples 9 2.2.3 Motion Vector Prediction 12 2.3 Intra Prediction 13 2.3.1 44 Luma Prediction Modes 14 2.3.2 1616 Luma Prediction Modes 15 2.3.3 88 Chroma Prediction Modes 16 2.4 Transform and Quantization 16 2.4.1 44 Residual Transform and Quantization (blocks 0-15, 18-25) 17 2.4.1.1 Development from the 44 DCT 18 2.4.1.2 Quantization 19 2.4.1.3 Rescaling 22 2.4.2 44 Luma DC Coefficient Transform and Quantization (1616 Intra-mode Only) 23 2.4.3 22 Chroma DC Coefficient Transform and Quantization 25 2.4.4 The Complete Transform, Quantization, Rescaling and Inverse Transform Process 26 2.5 Deblocking Filter 27 2.5.1 Boundary Strength 29 2.5.2 Filter Decision 30 2.5.3 Filter Implementation 30 Chapter 3 Fast Mode Decision for Intra Prediction 32 3.1 Overview of Fast Intra Prediction 32 3.2 Edge Map 33 3.3 Edge Direction Histogram 34 3.3.1 Edge Direction Histogram for 44 Luma Block 34 3.3.2 Edge direction histogram for 1616 luma and 88 chroma block 36 3.4 Histogram based fast mode selection for intra prediction 37 3.4.1 44 luma block prediction modes 37 3.4.2 1616 luma block prediction modes 37 3.4.3 88 chroma prediction modes 37 3.5 Observation 38 Chapter 4 Fast Intermode Decision 39 4.1 Lagrangian Cost for Intermode 39 4.2 Determination of Homogenity and Stationarity 42 4.3 Fast Intermode Decision Algorithm 43 4.4 Observation 44 Chapter 5 Fast Motion Estimation 46 5.1 Overview of Motion Estimation 46 5.2 Unsymmetrical Cross Multi Hexagon Grid Search (UMHexagonS) Algorithm 47 5.3 Center Biased Fractional Pel Search (CBFPS) Algorithm 49 5.4 Observation 51 Chapter 6 Enhanced Block Motion Estimation 52 6.1 Dynamic Threshold Determination 52 6.2 Enhanced Block Motion Estimation Algorithm 54 6.3 Overall algorithm 55 Chapter 7 Experimental Results 57 7.1 Experimental Results on IPPP Sequences 59 7.2 Experimental Results on IBBP Sequences 62 7.3 Comparison curves for Sequences 64 Chapter 8 Conclusion 67 References 68

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