Bayesian wavelet shrinkage with edge detection for SAR image despeckling

被引：118
|
作者：
Dai, M [1 ]
Peng, C
Chan, AK
Loguinov, D
机构：
[1] Texas A&M Univ, Dept Elect Engn, College Stn, TX 77843 USA
[2] Texas A&M Univ, Dept Comp Sci, College Stn, TX 77843 USA
来源：
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2004年 / 42卷 / 08期
关键词：
minimum mean square error (MMSE) estimation; ratio edge detector; stationary wavelet transform (SWT); wavelet shrinkage;
D O I：
10.1109/TGRS.2004.831231
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
In this paper, we present a wavelet-based despeckling method for synthetic aperture radar images and derive a Bayesian wavelet shrinkage factor to estimate noise-free wavelet coefficients. To preserve edges during despeckling, we apply a modified ratio edge detector to the original image and use the obtained edge information in our despeckling framework. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test images.
引用
收藏
页码：1642 / 1648
页数：7
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