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研究生:李宗澔
研究生(外文):Tsung-hao Li
論文名稱:基於視覺最佳化之JPEG2000的彩色立體影像編碼研究
論文名稱(外文):STEREOSCOPIC COLOR IMAGE CODING BASED ON PERCEPTUALLY OPTIMIZED JPEG2000 CODER
指導教授:周俊賢周俊賢引用關係
指導教授(外文):Chun-hsien Chou
學位類別:碩士
校院名稱:大同大學
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:2005
畢業學年度:93
語文別:英文
論文頁數:82
中文關鍵詞:立體影像視覺編碼
外文關鍵詞:JPEG2000perceptual codingstereoscopic image
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隨著近幾年來顯像技術的發展,在三度空間上的影像系統越來越熱門。3D 立體
影像和2D 影像比較起來最明顯的差異就是多了景深,而一個最容易得到具有深度
的視覺感知立體影像的方法,便是讓觀看者的左眼看到立體影像對中的左眼影像,
右眼看到右眼影像。因為立體影像對中的兩張影像是針對相同景物的些微視差得到
的,所以在其中有著相當多的重複資訊,因此,一個好的立體影像資料壓縮演算法
必須有效地移除各種視覺贅餘量。在本篇論文中,我們提出一個經由視覺最佳化的
彩色立體影像演算法,此演算法在低位元率的要求下,不僅可以移除單張影像中的
統計和視覺贅餘量,而且可以減少立體影像中本來就存在的視覺贅餘量。
依照人眼對於立體影像的感知特性,我們只要能確保其中一張影像的視覺品質,即
使另一張影像的視覺品質較差,也能得到整體視覺品質不錯的立體影像。因此我們
針對立體影像對中的左眼影像,使用了利用人眼視覺特性最佳化過的JPEG2000 編
碼。 因為JPEG2000 是一種符合ISO/ITU 標準的新靜態影像壓縮技術,由於其多重
解析(Multi-resolution)小波分解及雙層式(Two-tier)編碼架構非常適合將人類視
覺模型加入其編碼演算法中。右眼影像是經由立體視差估測法(Disparity Estima-
tion)估測而得,由此預估而得的影像和原始的右眼影像,可得到一殘留影像,因
為我們只需要一張視覺品質不錯的影像即可,所以這張殘留 影像便可只針對視覺
上的重要訊號作編碼即可。
根據模擬的結果,在0.2bpp 的平均位元率下,可重建出一人眼可接受的視覺品質
之立體影像。而其PSNR 及PSPNR 分別為33dB 和38dB。其結果證實,我們所提出
的演算法不僅在視覺品質上有不錯的表現,而且有效地增進了編碼的效能。
Through the development of the display technology in these years, the 3-D image
system has become more and more popular. The most obvious difference between 3-D
and 2-D image is the depth of perception. One of the easiest ways to retrieve a vision with depth is to let the viewer see the left-view image in the image pair with the left eye, and vice versa. Because a stereoscopic image is generated with slight differences in viewing the same scene from different perspectives, lots of stereoscopic visual redundancies actually exist. Therefore, a good stereoscopic algorithm should be able to remove various
kinds of redundancies.
In this thesis, we present a stereoscopic color image coder based on perceptually optimized JPEG2000. This algorithm can not only remove the statistical and visual redundancies in single image, but also the stereoscopic visual redundancies that exist inherently in stereo pairs.
According to the characteristic of human visual perception of stereo images, we can perceive an acceptable visual quality of the stereo pair as the visual quality of one image in the pair is assured. Therefore, the perceptually optimized JPEG2000 coder is exploited in the left-view image in the stereoscopic pair during researches. Because JPEG2000 is the new ISO/ITU standard for still image compression. The multi-resolution wavelet
decomposition and the two-tier coding structure of JPEG2000 fit in incorporating the human visual model into the coding algorithm. The right-view image of the stereo pair is predicted by disparity estimation. With the right-view image and the predicted image, we can generate a residual. Because we only need a decent visual quality, the residual will only encode the vital information which will affect visual quality.
Simulation results show that the acceptable visual quality can be obtained at an
average bit rate of 0.21 bpp with PSNR and PSPNR equal to 33 dB and 38 dB
respectively. The result shows that our proposed algorithm not only has a good visual quality but also improved the coding efficiency.
ABSTRACT (in Chinese) Ⅰ
ABSTRACT (in English) Ⅱ
ACKNOWLEDGEMENT Ⅲ
CONTENTS Ⅳ
LIST OF FIGURES Ⅵ
LIST OF TABLES Ⅷ
CHAPTER 1 INTRODUCTION 1
1.1 Motivation 1
1.2 Perceptual Coding 2
1.3 Objective 4
1.4 Approaches of the Proposed Coding Algorithm 4
1.5 Organization of this Thesis 5
CHAPTER 2 THE PERCEPTUAL MODEL FOR ESTIMATING JND PROFILES 6
2.1 Basic Structure of the Proposed Perceptual Model 6
2.2 JND Profile Estimation for Luminance Signals 7
2.2.1 Contrast sensitivity 8
2.2.2 Texture masking 11
2.2.3 Spatial JND profile for luminance signals 13
2.3 JND Profile Estimation for Chrominance Signals 16
2.3.1 JNCD in an ideal uniform color space 16
2.3.2 Intercomponent masking effect 19
2.3.3 Spatial JND profiles estimation for chrominance signals 21
2.4 Verification of the Perceptual Model 30
CHAPTER 3 THE PROPOSED STEREOSCOPIC COLOR IMAGE CODEC 33
3.1 Basic Structure of the Proposed Stereoscopic Image Coder 33
3.2 Coding of Left-View Image 34
3.2.1 Distortion Allocation of JND Profiles 36
3.2.2 Distortion allocation for luminance signals 39
3.2.3 Distortion Allocation for chrominance signals 40
3.2.4 Rate-distortion Optimization 43
3.2.5 Perceptual Distortion Evaluation 44
3.2.6 Perceptible Rate-distortion Rate Control 45
3.2.7 Perceptually Optimized JPEG2000 Encoder 46
3.3. Coding of Right-View Image 48
CHAPTER 4 STEREOSCOPIC VISION 49
4.1 Stereoscopic Vision 49
4.1.1 Application of stereo image 49
4.1.2 Stereoscopic vision 49
4.2 Background 50
4.2.1 Optical geometry 50
4.2.2 Two types of disparity estimation algorithm 51
4.3 Theory of Stereo Image Coding 52
4.3.1 Conditional coder (CONCOD) 53
4.3.2 Rate-distortion problem 53
4.4 Disparity compensation 54
CHAPTER 5 SIMULATION RESULTS 56
5.1 Conditions in Simulation 56
5.2 Fidelity Measure Criterion 58
5.3 Experimental Results 59
5.3.1 Coding of left-view images 60
5.3.2 Coding of right-view images 68
5.3.2.1 The right-view image predicted by disparity estimation from the reconstructed left-view image 68
5.3.2.2 Perceptually tuned JPEG2000 encoder 69
5.3.2.3 Performance of the right-view image 73
5.3.3 Performance of the proposed coder 73
CHAPTER 6 CONCLUSIONS 78
REFERENCES 79
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