M带小波变换在图象中的应用
APPLICATION OF M-BAND WAVELET TRANSFORM TO IMAGES
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摘要: 小波变换是近年来兴起的一种时频域信号分析理论,是信号分析处理的一种强有力的新工具.本文根据小波变换的特点,在Mallat二带多分辨分析的基础上,讨论分析了信号的多带多分辨分析的理论和实现算法,并将这一理论和算法应用于图象处理,取得了满意效果.Abstract: Wavelet transform, especially the multiresolution representation, is a very effective tool for analyzing the information contents of a signal. Based on Mallat s multiresolution analysis, this paper discusses the theoretical analysis of M-band multiresolution signal decomposition, proposes a new algorithm for realizing the theory, studies the properties of an operator which approximates a signal at a given resolution, and applies the theory to images. The results show that, first, images can be decomposed and reconstructed by M-band multiresolution representation; second, the edges of image can be detected by M-band wavelet transform.
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Jawerth B Sweldens W. An overview of wavelet based multiresolution analysis[J].SIAM.1994, 36(3):377-412[2][2][3]Daubechines I. Orthonormal bases of compactly supported wavelet[J].Commu. Pure Appl.1988, 41(2):909-996[4]Mallat S G. Multifrequency channel decompositions of images and wavelet models[J].IEEE Trans. on ASSP.1989, 37(12):2091-2110[5]Zou hI, Tewfik A H. Discrete orthogonal M-band wavelet decomposition. In proc. ICASSP, San. Franciso: 1992, 4(iv): 605-608.[6]Steffen P, Heller P N, Gopinuth R A. Theory of regular M-band wavelet bases[J].IEEE Trans. on SP.1993, 41(12):3497-3511[7]Mallat S G. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. on PAMI, 1989, 11(11): 674-693.[8]Mallat S G. Characterization of signals from multiscale edges. IEEE trans. PAMI, 1992, 14(7): 710-732.[9]马尔D著,姚国正,等译.视觉计算理论.北京:科学出版社,1988, 40-281.[10]Ikonomopouls A, Kunt M. High compression image coding via directonal filtering. Signal Processing, 1985; 8(1): 179-203. -
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