文章基本信息

标题：Bayesian-based Despeckling in Wavelet Domain Using "a Trous" Algorithm
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作者：H.A. Moghaddam ; M.J.V. Zouj ; M. Dehghani 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2004
卷号：XXXV Part B7
页码：27-31
出版社：Copernicus Publications
摘要：In this paper an improved speckle noise reduction method is presented based on wavelet transform. A 2D Gaussian function is found to be the best model fitted to the speckle noise pattern cross-section in the logarithmically transformed noisy image. Therefore, a Gaussian low pass filter using a trous algorithm has been used to decompose the logarithmically transformed image. A Bayesian estimator is then applied to the decomposed data to estimate the best value for the noise-free wavelet coefficients. This estimation is based on alpha-stable and Gaussian distribution hypotheses for wavelet coefficients of the signal and noise, respectively. Quantitative and qualitative comparisons of the results obtained by the new method with the results achieved from the other speckle noise reduction techniques demonstrate its higher performance for speckle reduction in SAR images
关键词：Transformation; Estimation; SAR; Radar; Statistics; Multiresolution