臺灣博碩士論文加值系統

　　近年來小波轉換用於影像壓縮技術上已經有相當成熟的研究。由Shapiro提出的嵌入式零數編碼法(EZW)以及由Said和Pealman所提出的分集階層樹編碼法(SPIHT)均展示出以小波轉換為基礎的影像壓縮具較佳的效能。而這兩種演算法被延伸至視訊壓縮技術，亦展現極佳的效能。然而在低位元率的情況下，整個還原的影片畫面中，包括人眼敏感及人眼不敏感的區域，都會有很低的品質。為了改善這個問題，本論文提出自畫面中人眼比較不敏感的區域，即影片中動態區域，分配位元給畫面中人眼比較敏感的區域，即影片中靜態區域，使得人眼比較敏感的區域有較高的精確度，讓還原的影片在同樣的位元率下能產生較佳的視覺效果。但是，在分配靜態區域的位元給動態區域時，維持靜態區域的品質對於影片的視覺效果是必要的。為了探討這個問題，本論文也提出了一個基於人眼接受程度的位元分配機制，以達到最佳的視覺效果。

　In recent years, wavelet transform has become a mature technique in image compression. The embedded zero-tree wavelet (EZW) by Shapiro, and its modification, namely set partitioning in hierarchical trees (SPIHT) by Said and Pealman, demonstrates the competitive performance of wavelet-based compression schemes. These two algorithms have been extended to video coding compression, and shown excellent performance. However in low bit rate situations, on the whole the reconstructed videos containing eye-sensitive and eye-insensitive regions have low quality. To improve this problem, this thesis proposes to rearrange bit rates from eye-sensitive regions which is the motion of the video to eye-insensitive regions which is the static regions of the video, so that eye-sensitive regions would have higher fidelity so as to obtain a better visual condition on the whole video. Nevertheless, properly rearranging background bits to motion regions while maintaining the quality of the background is necessary for visual condition of the video. To address this issue, this thesis also proposes a Bit Arrangement scheme based on the acceptability of the human eyes to achieve best visual condition.

Chapter 1 Introduction...1
Chapter 2 Wavelet Transform and SPIHT Algorithm...5
2-1 Wavelet Transform...7
2-1-1 Discrete Wavelet Transform...7
2-1-2 2-D and 3-D Discrete Wavelet Transform...11
2-2 SPIHT Algorithm...14
2-2-1 Genealogy of SPIHT...14
2-2-2 Zero-tree and Lists in SPIHT...17
2-2-3 Algorithm Procedure...18
2-3 3-D SPIHT Algorithms...21
2-3-1 Conventional 3-D SPIHT...21
2-3-2 ERC-SPIHT...23
Chapter 3 Motion Emphasis 3-D SPIHT...27
3-1 Coding Scheme of the ME-SPIHT...28
3-2 Motion Detection...30
3-3 Bit Arrangement...32
3-4 Data Structure of the ME-SPIHT...33
Chapter 4 Bit Arrangement in ME-SPIHT...37
4-1 Examinations for Human Acceptability...38
4-2 Model of Acceptable Boundary...42
4-3 Kanada-Lucas-Tomasi Algorithm...44
4-4 Estimation of Initial-Translated Bit Rate...47
4-5 Estimation of Adjustment Function...49
4-6 Bit Arrangement Procedure...53
Chapter 5 Experiment Results...55
5-1 Coding Results of Training Data...56
5-2 Coding Results of Testing Data...61
Chapter 6 Conclusion and Future Work...65
Reference ...67
Appendix...71

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