臺灣博碩士論文加值系統

近年來3D立體影片越來越流行，其資料量相較於傳統2D影片來的龐大許多，而使用多視角影片加上其對應之多視角深度圖 (MVD) 格式，再利用基於深度影像之繪圖法 (DIBR)，即可有效地傳送或儲存3D影片。傳統上在深度圖壓縮時的位元率及失真最佳化 (RDO) 過程中，直接考慮深度圖本身的失真。然而在實際應用中深度圖並不會直接被使用者觀看，它只是DIBR所需的輔助資訊而已。所以後來有人認為考慮合成視角的失真是比較好的做法。在本篇論文之中，我們從頻率域的角度去分析深度圖壓縮所產生的失真對合成視角之失真的影響，並提出一個基於合成視角失真估計的深度圖失真評估準則，取代傳統的RDO過程。實驗結果顯示我們的方法可以比傳統的RDO過程節省45% BDBR。

3D video becomes more and more popular recent years. The multi-view video plus depth (MVD) format assisted with depth-image-based rendering (DIBR) technique is an efficient representation of 3D video. Conventionally in depth map coding, the distortion in the rate-distortion optimization (RDO) procedure is only measured with the sum of squared differences (SSD) of depth map. But depth map is just a supplementary data for view synthesis. So the quality of depth map is not highly correlated with the quality of the synthesized view, instead we should take the quality of synthesized view into consideration in the RDO procedure. In this thesis, the relationship between the synthesized view distortion and the depth coding error is analyzed in the frequency domain. Thus an efficient depth map coding based on a new distortion metric is proposed. Then in the RDO procedure, the depth distortion is replaced by the estimated synthesized view distortion. The simulation results show that the proposed distortion metric could achieve about 45% BDBR saving for depth data compared to the conventional scheme.

摘 要 I
ABSTRACT II
誌謝 III
CONTENTS IV
LIST OF TABLES VI
LIST OF FIGURES VII
1. INTRODUCTION 1
1.1 Research Background 1
1.2 Motivation 4
1.3 Thesis Organization 6
2. OVERVIEW OF HEVC AND 3D-HEVC 7
2.1 Basic Concepts of HEVC 7
2.1.1 Coding Structure 8
2.1.2 Prediction Modes 10
2.1.3 Rate-Distortion Optimization (RDO) 13
2.2 Basic Concepts of 3D-HEVC 14
2.2.1 Coding of Color Images 15
2.2.2 Coding of Depth Maps 19
3. RELATED WORK 22
3.1 SVDC 23
3.2 Frame-Wise Approach 26
3.3 Block-Wise Approach 28
3.4 Pixel-Wise Approach 30
4. THE PROPOSED DISTORTION METRIC OF DEPTH MAP CODING 34
4.1 Concepts 34
4.2 Analysis of the Depth Error and the Synthesized View Distortion 36
4.2.1 Depth Errors to Position Errors 36
4.2.2 Positions Errors to the Synthesized View Distortion 42
4.3 Procedures of the Proposed Distortion Metric 48
5. SIMULATION RESULTS 49
5.1 Simulation Settings 49
5.2 Comparison of Coding Efficiencies 52
6. CONCLUSIONS AND FUTURE WORK 56
REFERENCES 57

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