SAR Images Despeckling Based on Bayesian Estimation and Fuzzy Shrinkage in Wavelet Domains  

基于小波域贝叶斯估计模糊萎缩的SAR图像降斑算法(英文)

作　　者：吴艳 王霞 廖桂生 

机构地区：[1]National Key Lab. of Radar Signal Processing, Xidian University [2]School of Electronics Engineering, Xidian University, Xi'an 710071, China [3]School of Electronics Engineering, Xidian University

出　　处：《Chinese Journal of Aeronautics》2006年第4期326-333,共8页中国航空学报（英文版）

基　　金：A Postdoctoral Science Foundation of China (J63104020156); National Defence Foundation of China

摘　　要：An efficient despeclding algorithm is proposed based on stationary wavelet transform （SWT） for synthetic aperture radar （SAR） images. The statistical model of wavelet coefficients is analyzed and its performance is modeled with a mixture density of two zero-mean Gaussian distributions. A fuzzy shrinkage factor is derived based on the minimum mean square error （MMSE） criteria with Bayesian estimation. In the case above, the ideas of region division and fuzzy shrinkage arc adopted according to the interscale dependencies among wavelet coefficients. The noise-free wavelet coefficients are estimated accurately. Experimental results show that the algorithm proposed is superior to the refined Lee filter, wavelet soft thresbolding shrinkage and SWT shrinkage algorithms in terms of smoothing effects and edges preservation.An efficient despeclding algorithm is proposed based on stationary wavelet transform （SWT） for synthetic aperture radar （SAR） images. The statistical model of wavelet coefficients is analyzed and its performance is modeled with a mixture density of two zero-mean Gaussian distributions. A fuzzy shrinkage factor is derived based on the minimum mean square error （MMSE） criteria with Bayesian estimation. In the case above, the ideas of region division and fuzzy shrinkage arc adopted according to the interscale dependencies among wavelet coefficients. The noise-free wavelet coefficients are estimated accurately. Experimental results show that the algorithm proposed is superior to the refined Lee filter, wavelet soft thresbolding shrinkage and SWT shrinkage algorithms in terms of smoothing effects and edges preservation.

关 键 词：SAR image despeclding fuzzy shrinkage factor MMSE region division. Bayesian estimation SWT 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]