臺灣博碩士論文加值系統

本論文首要是對醫學影像利用小波來壓縮編碼進行研究，並且是假設在傳輸通道無雜訊及無誤差條件下，應用於醫學影像的壓縮上。為了要增加在影像的壓縮比率，所以將小波轉換後的小波係數經過向量量化後再來進行壓縮，因為使用向量量化的主要原因是由於它具有很高的壓縮比率，所以在解壓縮時也相當容易。在研究裏提出用四分樹分割法作為在影像的前處理，把影像的細節和背景部份分割成尺寸大小不同的區塊，再經小波轉換後將每一個子頻帶區塊的小波係數能量值(variance)，來做為位元分配的依據。由分配到的位元選擇最適當的編碼簿(codebook)，並且編碼後得到的失真值來調整位元率，因為切割影像區塊的像素差異性較低，所以可增快向量量化編碼的速度進而改善影像壓縮之效能。

關鍵字：小波轉換、四分樹、向量量化。

Wavelet transform technique is widely used in image compression because it provides a multiresolution representation of images. With vector quantization algorithm, the wavelet transformed coefficients can be compressed further. In this study, we have proposed a quadtree segmentation method for medical image preprocess. Quadtree segmentation algorithm is used to divide a given MRI medical image, where regions with image detail will be segmented into blocks with smaller block size, and the background of the image will be assigned larger block size. Choosing proper size of vector quantized codebook after the wavelet transform, we have applied bit allocation assignment associated with the variance of each sub band image block. For this proposed medical image compression scheme, simulation results show acceptable visual quality and good compression ratio simultaneously. Furthermore, due to the codebook size been reduced, we are able to save the computational time. System performance analysis is also demonstrated in this thesis.

Key Words : Quadtree Segmentation, Wavelet Transform

第一章 緒論
1.1 前言------------------------------------------------------------------------------1
1.2 研究動機------------------------------------------------------------------------2
1.3 研究目的------------------------------------------------------------------------3
1.4 論文架構------------------------------------------------------------------------4
第二章 可變動影像區塊四分樹分割法
2.1 前言------------------------------------------------------------------------------5
2.2 影像分割的目的---------------------------------------------------------------6
2.3 四分樹影像分割法------------------------------------------------------------8
2.4 四分樹影像分割法結果比較-----------------------------------------------11
第三章 小波轉換與位元分配
3.1 前言----------------------------------------------------------------------------14
3.2 離散小波轉換----------------------------------------------------------------15
3.3 位元分配----------------------------------------------------------------------22
第四章 向量量化
4.1 前言----------------------------------------------------------------------------24
4.2 向量量化----------------------------------------------------------------------24
4.3 編碼簿之產生----------------------------------------------------------------28
第五章模擬結果與分析
5.1 失真壓縮系統的評估方式-------------------------------------------------31
5.2 模擬結果----------------------------------------------------------------------32
第六章 結論與未來展望
6.1 結論----------------------------------------------------------------------------58
6.2 未來展望----------------------------------------------------------------------59
參考文獻----------------------------------------------------------------------------60

[1] A. Gersho and R. M. Gray, “Vector Quantization and Signal Processing,” Kluwer Academic Publishers, 1991.
[2] A. Gersho, “On the Structure of Vector Quantizers,” IEEE Trans. On Inform. Theory, vol. 28, no. 2, pp. 157-162, Mar. 1982.
[3] A. K. Jain, “Fundamemtal of Digital Image Processing,” Prestice-Hall, Englewood Cliffs, NJ, 1989.
[4] M. Antonini, M. Barlaud, P. Mathieu, and I. Daubechies, “Image Coding Using Wavelet Transform,” Image Processing, IEEE Transactions on, volume: 1 issue: 2 , Apr 1992.
[5] Ching Yang Wang, Shih Jao Liao, and Long Wen Chang, “Wavelet Transform Coding Using Variable Blocksize Vector Quantization with Optimal Quadtree Segmentation,” TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications', Proceedings of IEEE, volume: 2 , 2-4 Dec 1997.
[6] C.-T. Chen, “Adaptive Transform Coding via Quadtree-Based Variable Blocksize DCT,” In Proc. IEEE Int. Conf. Acoust., Speech, Signal Processing, pp. 1854-1857, 1989.
[7] G. J. Sullivan and R. L. Baker, “Efficient Quadtree Coding of Images and Video,” IEEE Trans. Image Processing, vol. 3, pp. 327-331, May 1994.
[8] N. Mohsenian and N. M. Nasrabadi, “Edge-Based Subband VQ Techniques for Images and Video,” Circuits and Systems for Video Technology, IEEE Transactions on, volume: 4, pp. 53-67 issue: 1 , Feb 1994.
[9] N. M. Nasrabadi and R. A. King, “Image Coding Using Vector Quantization : a Review,” IEEE Trans. On Communication, vol. 36, no. 8, pp. 957-971, Aug. 1988.
[10] K. Ramchandran and M. Vetterli, “Best Wavelet Packet Bases in a Rate-Distortion Sense,” Image Processing, IEEE Transactions on, volume: 2 issue: 2 , pp. 160-175 Apr 1993.
[11] Y. Shoham and A. Gersho, “Efficient Bit Allocation for an Arbitrary Set of Quantizers,” IEEE Trans. Acoustics, Speech, and Signal

[12] Processing, vol. 36, pp. 1445-1453, September 1988.
[13] J. Vaisey and A. Gersho, “Variable Block-Size Image Coding,” Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '87., volume: 12 , pp. 1051-1054 Apr 1987.
[14] J. Vaisey and A. Gersho, “Image Compression with Variable Block Size Segmentation,” Signal Processing, IEEE Transactions on, volume: 40 issue: 8 , pp. 2040-2060 Aug 1992.
[15] R. M. Gray, “Vector Quantization,” IEEE Acoust., Speech, Signal Processing Magazine, Apr. 1984.
[16] R. C. Gonzalez and P. Wintz, “Digital Image Processing,” Addison Wesley,Reading,MA,1997.
[17] C. Y. Teng and D. L. Neuhoff, “A New Quadtree Predictive Image Coder,” image processing 1995 . Proceeding, international Conference on, vol.2 , pp. 73 – 76 , 1995.
[18] R. Distasi, M. Nappi and S. Vitulano, “Image Compression by B-Tree Triangular Coding,” IEEE Trans on Commu, vol.45,no.9 ,pp. 1095-1100,Sep.1997.
[19] J. C. Wu and D. G. Daut, “Adaptive Non-Stationary DPCM Image Coding with Variable Blocksize,” in the 1997 symposium on Visual Communications and Image Processing, SPIE vol. 3024,pp. 447-458,Feb.1997.
[20] O. Rioul and M. Vetterli, “Wavelets and Signal Processing,” IEEE Signal Processing Magazine, October 1991, pp. 14-35.
[21] W. K. Pratt, “Digital Image Processing,” Wiley-Interscience, New York, 1978.
[22] R C. Gonzalez and R E. Woods, “Digital Image Processing,” Addison-Wesley Publishing Company, 1992.
[23] B. Porat, “A Course in Digital Signal Processing,” John Wiley & Sons, 1997.
[24] Y. Linde, A. Buzo and R. M. Gray, “An Algorithm for Vector Quantizer Design,” IEEE Trans. on Communication, vol. COM-28, no. 1, pp. 84-95, Jan. 1980.
[25] L. Torres and J. Huguet, “An Improvement on Codebook Search for Vector Quantization,” IEEE Trans. on Communication, vol. 42, no. 2/3/4, Feb. 1994.
[26] S. Mallat, “A Theory for Multiresolution Signal Decomposition: the Wavelet Representation,” IEEE Trans. on tern Analysis and Machine Intel, vol-11, no. 7, pp. 674-693, July 1989.
[27] P. H. Westerink, D. E. Boekee, J. Biemond and J. W. Woods, “Subband Coding of Images Using Vector Quantization,” IEEE Trans. Comm, COM-36(6), 713-719, 1988.
[28] M. Vetterli and C. Herley, “Wavelets and Filter Banks: Theory and Design,” IEEE Trans. Sig. Proc, Sept. 1992, pp. 2207-2232.
[29] Yu-Chen Hu and Chin-Chen Chang, “Variable Rate Vector Quantization Scheme Based on Quadtree Segmentation,” Consumer Electronics, IEEE Transactions on, volume: 45 issue: 2, pp. 310-317 May 1999.
[30] 李朝欽, “Image Fusion Using Wavelet Transform with Quadtree Segmentation,” 大葉大學電機工程系碩士論文, June, 2001.
[31] 邱俊德, “Image Compression by Self-Organized Kohonen Map,” 大葉大學電機工程系碩士論文, June, 1999.
[32] 賴健文, “The Study of Variable Block Size DP-DPCM Image Coding Algorithm for Medical Image Compression,” 大葉大學電機工程系碩士論文, June, 2003.
[33] 施銘鎧, “Variable Blocksize Wavelet Transform Image Coding,” 大葉大學電機工程系碩士論文, June, 2003.
[34] 魏宏諺, “Fixed Blocksize Wavelet Image Transmission Over MIMO System,” 國立海洋大學通訊與導航工程系碩士論文, July, 2009.
[35] 卓珊琪, “Image Segmentation and Watermarking Hiding Algorithm,” 國立海洋大學通訊與導航工程系碩士論文, July, 2009.