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研究生:溫正成
研究生(外文):Weng, Cheng-Cheng
論文名稱:基於參數化位元率失真準則對小波分解影像
論文名稱(外文):Joint Source-Channel Coding of Wavelet-Decomposed Images with Parameterized Rate-Distortion Optimization
指導教授:賴坤財
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:電子工程系
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:2001
畢業學年度:89
語文別:英文
論文頁數:96
中文關鍵詞:合併式訊源與通道編碼小波位元率失真最佳化
外文關鍵詞:joint source-channel codingwaveletrate-distortion optimization
相關次數:
  • 被引用被引用:1
  • 點閱點閱:244
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
這篇論文針對小波分解的影像而發展合併式訊源與通道的編碼。由於一張影像的失真是來自於量化與傳送的過程中,我們可以將影像的失真看做是訊源編碼位元與通道編碼位元的函數。在作訊源編碼時,我們採用針對機率分佈函數作最佳化的非均勻量化方法以獲得更精確的量化結果。在這篇論文中,我們也可看到針對Gauss與Laplace機率分佈作最佳化的量化器,同時也針對不同的量化階數計算出這兩種量化器的量化邊界與量化值。
我們可看到小波封包分解運用於影像壓縮時的特性與彈性,我們也利用參數化的位元率失真準則來產生最佳的小波封包基底,而能夠在有限的位元預算下,將影像所受到的失真降到最低。
運用位元率失真準則,我們將可同時找出最佳小波封包基底與其相對的最佳訊源與通道編碼的選擇。每張小波分解而來的子影像都有不同的平均值與變異量。運用等斜率位元分配的原則,我們將可針對每張子影像選擇其最佳的位元分配情形,因而可使失真降到最低。
最後我們將對合併式訊源與通道編碼和只做訊源編碼的情形作一比較,實驗的結果顯示我們所提出的方法無論在訊雜比值(SNR)上或視覺感官上都可獲得較佳的結果。
A joint source-channel coding scheme is developed for wavelet-decomposed images. The distortion suffered by the image is induced by the quantization and transmission processes. We derive the distortion as a function of the source coding and channel-coding rate. In the source coding, we use the nonuniform pdf-optimized quantization to give more accurate quantization than the uniform quantizer for a given quantization level. We also get the reconstruction levels, decision boundaries, and distortion for Gaussian- and Laplacian-optimized quantizers.
The flexibility and characteristics of wavelet packet decomposition in image compression is studied, and we utilize the parameterized rate-distortion optimization to generate the best wavelet packet basis that can minimize the total distortion suffered by the image for the constraint of a given rate budget.
The rate-distortion criterion is presented and used to find the best wavelet packet basis and its optimal source-channel coding choice jointly. Each wavelet-decomposed subimage has a particular mean and variance. We use the equal slope rate allocation policy to select the optimal rate allocation for each subimage. Under the optimal allocation of source-coding and channel-coding rate, the total distortion suffered by the image can be minimized.
Finally, we compare the performance of this joint source-channel coding system with that obtained from the source-only coding case. Experimental results show that the proposed coding scheme is better than the source-only coding system, as evaluated both mathematically (in terms of signal-to-noise ratio) and visually.
Chapter 1 Introduction……….………………………………………………...1
1.1Overview……………………………………………………………………1
1.2Architecture of the Thesis…………………………………………………..2
Chapter 2 Review on Previous Work……………….………………………….4
2.1The Fundamentals of Quantization…………………………………………4
2.2Nonuniform Pdf-Optimized Quantization…………………………………..8
2.3Subband Coding…………………………………………………………...11
2.4Wavelet Packet……………………………………………………….……16
2.4.1Historical Review……………………………………………….16
2.4.2Wavelet Transform……………………………………………...16
2.4.3Multiresolution Analysis………………………………………..20
2.4.4Digital Implementation of Wavelet Decomposition…………….23
2.4.5Reconstruction from Decomposed Coefficients………………...25
2.4.6Choosing the Wavelets………………………………………….26
2.4.7Wavelet Packets……………………………………….………..28
Chapter 3 Joint Source-Channel Coding of Wavelet-Decomposed Images..33
3.1Two-Dimensional Wavelet Analysis in the Image Compression…….……33
3.2Rate-Distortion Theory………………………………………………..…..40
3.3Joint Source-Channel Coding……………………………………………..41
3.3.1Basic Conceptions of Joint Source-Channel Coding……...41
3.3.2Design of the Joint Source-Channel Coding………………43
3.3.2.1Pdf-Optimized Quantizer…………………………….43
3.3.2.2Channel Coding………………………………………51
3.4Best Wavelet Packet Bases with Rate-Distortion Criterion……………….57
3.4.1Decomposing the Image with Rate-Distortion Optimization…..58
3.4.2Channel Models…………………………………………………63
3.4.2.1Discrete Memoryless Channel……………………………..63
3.4.2.2Binary Symmetric Channel…………………………..……64
3.4.2.3Gaussian Channel………………………………………….65
3.4.3Distortion Analysis……………………………………………...67
Chapter 4 Experiments and Results………………………………………….75
4.1Rate-Distortion Curves and Bits Allocation………………………………75
4.2Coding Results…………………………………………………………….80
Chapter 5 Conclusions…..…………………………………………………….93
5.1Conclusions………………………………………………………………..93
5.2Future Works………………………………………………………………94
References………………………………………………………………………95
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