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研究生： 陳怡伶
Chen, Yi-ling
論文名稱： 利用邊界偵測之可調式去方塊效應演算法
An Adaptive Deblocking Algorithm with Boundary Detections
指導教授： 戴顯權
Tai, Shen-chuan
學位類別： 碩士
Master
系所名稱： 電機資訊學院 - 電腦與通信工程研究所
Institute of Computer & Communication Engineering
論文出版年： 2008
畢業學年度： 96
語文別： 英文
論文頁數： 74
中文關鍵詞： 去方塊效應 、邊界偵測 、濾波器
外文關鍵詞： deblocking, filter, boundary detection
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    • 本論文提出一個適用於低位元率，以方塊為基底(block-based)的影像或影片之偵測方塊邊界、並去除方塊效應演算法。偵測階段是用來偵測去方塊效應框(deblocking frame)中方塊邊界(block boundary)的位置，其中包括方塊寬度、高度的測量，以及指出方塊邊界的位置。而去方塊效應演算法則是執行在偵測階段所偵測到的方塊邊界上。在此提出一個低計算量的去方塊效應演算法，它包括3個濾波器，分別為平滑模式(用於低頻區域)、複雜模式(用於高頻區域)、角落模式(用於4個鄰近方塊的角落)。而模式判斷程序是藉由觀察方塊邊界附近像素的變化情形，來判斷此區域是用於何種濾波
    器。本篇論文所提出的演算法在偵測區塊邊界上有很高的準確度，並且能去除大部分的方塊雜訊。

    A new method to detect block boundaries and remove blocking artifacts in low bit-rate block-based images and video sequences is proposed in this thesis. The detection stage is applied to detect the location of block boundaries in deblocking frames, including measuring the width and the height of blocks and locating where the boundaries are.
    The deblocking algorithm is applied to the block boundaries which are detected at the detection stage. A low-complexity deblocking filter with three modes is proposed, including smooth mode (for low-frequency regions), complex mode (for high-frequency
    regions), and corner mode (for corner of four adjacent blocks). The mode decision procedure is based on observing pixel behavior around the block boundaries. The
    proposed algorithm can detect the block boundary with high accuracy, and remove more blocking artifacts.

    Contents i List of Tables iii List of Figures v 1 Introduction 1 2 Related Work 4 2.1 Compression Standard . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.1.1 JPEG . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.1.2 MPEG-2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2.2 Blocking Artifacts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.3 Deblocking Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3.1 Signal Adaptive Filtering . . . . . . . . . . . . . . . . . . . . . 9 2.3.2 Deblocking Filter with Two Separate Modes . . . . . . . . . . . 14 2.3.3 Low Complexity Deblocking Method . . . . . . . . . . . . . . . 19 3 The Proposed Algorithm 27 3.1 Detection of Block Boundary . . . . . . . . . . . . . . . . . . . . . . . 28 3.1.1 Vertical Boundary . . . . . . . . . . . . . . . . . . . . . . . . . 29 3.1.2 Horizontal Boundary . . . . . . . . . . . . . . . . . . . . . . . . 32 3.2 Deblocking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 3.2.1 Mode Decision . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.2 Filtering Stage . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.2.3 Corner Outlier . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 4 Experimental Results 40 4.1 Peak signal-to-noise ratio(PSNR) . . . . . . . . . . . . . . . . . . . . . 40 4.2 Deblocking Measurement . . . . . . . . . . . . . . . . . . . . . . . . . . 41 4.3 Experimental Results in images . . . . . . . . . . . . . . . . . . . . . . 42 4.3.1 Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42 4.3.2 Deblocking with Boundary Detection . . . . . . . . . . . . . . . 47 5 Conclusion and Future Works 69 5.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 5.2 Future Works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 6 Conclusion and Future Work 71 6.1 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 6.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Curriculum Vitae 74

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