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研究生： 曾照峰
Tseng, Chao-Feng
論文名稱： 影像壓縮之演算法與架構
Algorithms and Architectures for Image Compression
指導教授： 賴源泰
Lai, Yen-Tai
學位類別： 博士
Doctor
系所名稱： 電機資訊學院 - 電機工程學系
Department of Electrical Engineering
論文出版年： 2016
畢業學年度： 104
語文別： 英文
論文頁數： 78
中文關鍵詞： 影像壓縮 、影像縮放 、影像處理 、快速演算法 、硬體架構設計 、HEVC 、JPEG XR 、H.264 、AVC
外文關鍵詞： image compression, image scaling, image processing, fast algorithms, HEVC, JPEG XR, H.264, AVC
相關次數： 點閱：121  下載：0 
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    • 本論文提出了數種影像壓縮之演算法及架構。針對HEVC，提出了快速編碼單元決定法，能縮小編碼單元深度的搜尋範圍，達到快速決定深度的目的。另外還提出了快速模式選擇法，當最可能模式為特定方向的組合時，本方法可以快速挑出要進行「碼率－失真度最佳化」程序的模式。針對JPEG XR編碼程序中較複雜的「影像交疊轉換」和「影像核心轉換」，本文提出了新的運算法，可以消除計算過程中資料相依性，使所有算式能同時執行。此外，本文也提出了採用新演算法的軟硬體共同設計編碼器架構。
    對H.264/AVC的畫面內預測，本文提出了快速模式選擇法及其硬體架構設計。該方法採用了一種低複雜度的演算法以快速偵測區塊方向。對畫面間預測，本文提出了適用於三步搜尋法的可變區塊大小移動預估之硬體架構。為了提高預算速度，採用了平行化架構，並使處理單元能藉由小區塊的運算結果來計算大區塊的「絕對差值總和」。對影像縮放，本文提出了自適性影像內插法。本方法會檢查像素是否在物件邊緣並依據結果選擇對應的內插法，達到維持影像畫質和邊緣銳利度的目的。

    In this dissertation, we propose several fast algorithms and architectures for image compression. For HEVC, we propose a fast coding unit (CU) decision method. The method can reduce search ranges of CU depth to determine the depth of current CU quickly. Besides, we propose a fast mode selection method. It can quickly determine the modes for rate-distortion optimization when the combination of most probable modes reveals the pattern direction. For JPEG XR, we propose new algorithms for photo overlap transform (POT) and photo core transform (PCT), the complicated parts of JPEG XR. The new algorithms eliminate data dependency, so that operations in POT and PCT can be executed in parallel. In addition, we propose a hardware–software co-design encoder architecture which adopts the new algorithms.
    For intra-prediction in H.264/AVC, we propose a fast mode selection approach which uses a fast direction detection with low computational complexity. Also, we propose a hardware architecture for this algorithm. For inter-prediction, we design a VLSI architecture for variable block size motion estimation with three step search algorithm. To improve the throughput, parallel architecture is adopted and the processing elements can compute the sums of absolute differences of larger blocks by using the results derived for 4x4 blocks. For image scaling, we propose an adaptive image interpolation algorithm. It checks whether there is an edge or not in the region around a pixel and selects an interpolation method. Therefore the method keeps the edges sharp and provides good image quality.

    List of Tables IX List of Figures XI Chapter 1 Introduction 1 1.1 Background and Motivation 1 1.2 Organization 3 Chapter 2 Fast Coding Unit Decision and Mode Selection for Intra-Frame Coding in HEVC 4 2.1 HEVC Overviews 4 2.1.1 Previous Works 4 2.1.2 Block Structure 6 2.1.3 Intra-Frame Prediction and Mode Selection 7 2.1.4 CU Size Decision 9 2.2 Fast Coding Unit Decision and Mode Selection 10 2.2.1 Early Skipping of Fast Coding Unit Decision Method 10 2.2.2 Early Termination of Fast Coding Unit Decision Method 13 2.2.3 Fast Mode Selection Method 17 2.3 Performance Verification and Comparisons 18 2.4 Summary 24 Chapter 3 A Hardware-Software Co-Design Architecture for JPEG XR Encoder 25 3.1 JPEG XR Overviews 25 3.1.1 Previous Works 25 3.1.2 Encoding Procedures 26 3.2 Proposed Algorithms and Architecture 30 3.2.1 Modified POT and PCT Algorithms 30 3.2.2 Basic Filters with Multiple Functions 34 3.2.3 Memory Saving Scheme 36 3.2.4 Hardware-Software Co-Design Architecture 38 3.3 Experimental Results and Comparisons 39 3.4 Summary 42 Chapter 4 Algorithms and Architectures for H.264 43 4.1 Fast Algorithm and VLSI Design for H.264 Intra-Prediction 43 4.1.1 Previous Works of Intra-Prediction 43 4.1.2 Rate-Distortion Optimization and Intra-Prediction 44 4.1.3 New Method and Architecture for Intra-Prediction 45 4.1.4 Experimental Results 48 4.2 A VLSI Architecture for TSS with VBSME 50 4.2.1 Previous Works of Inter-Prediction 50 4.2.2 New VLSI Architecture for Three-Step Search 51 4.2.3 Experimental Results 57 4.3 Summary 58 Chapter 5 Adaptive Image Scaling Based on Local Edge Directions 59 5.1 Previous Works 59 5.2 Adaptive Image Scaling Based on Local Edge Directions 60 5.2.1 Edge Detection 60 5.2.2 Edge-Directed Interpolation 63 5.3 Simulations and Comparisons 65 5.4 Summary 67 Chapter 6 Conclusions and Future Works 69 Reference 72 Publication List 77 Biography 78

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