一种新的SAR图像快速自适应去斑算法

李应岐; 何明一

doi:10.11834/jig.20080205

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专辑

一种新的SAR图像快速自适应去斑算法
A New Fast Adaptive Algorithm for Despeckling SAR Images
2008年13卷第2期页码：214
纸质出版：2008
DOI： 10.11834/jig.20080205
稿件说明：

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李应岐, 何明一. 一种新的SAR图像快速自适应去斑算法[J]. 中国图象图形学报, 2008,13(2):214. DOI： 10.11834/jig.20080205.

A New Fast Adaptive Algorithm for Despeckling SAR Images[J]. Journal of Image and Graphics, 2008, 13(2): 214. DOI： 10.11834/jig.20080205.

摘要

针对SAR图像斑点噪声的滤除，提出了一种新的基于Countourlet变换的快速自适应性噪声去除方法。鉴于SAR图像的Countourlet系数主要取决于斑点噪声和信号腐化，且呈现出很强的非高斯分布特性，据此，首先建立了SAR图像Countourlet系数的高斯混合分布解析模型；然后用每个系数的邻域系数通过估计其去斑收缩因子来实现系数的自适应收缩；最后对Lee滤波、Foster滤波、Gamma 滤波、小波、Curvelet和Contourlet变换的去斑性能进行了比较分析。实验结果表明，该新方法在保留细节和锐化图像的同时，能强有力地抑制斑点噪声。

Abstract

A new adaptive contourlet transform-based technique for speckle removal from SAR images is presented. The distribution of the SAR image’s contourlet coefficients is mainly decided by speckle noise and useful signals corrupted. The analytic model for these distributions is proposed. The shrinkage factor for de-specking is estimated with the neighboring reference contourlet coefficient in every sub bands. Finally

the comparison of performance of Lee filter

Froster filter

Gamma filter

wavelet-based de-speckling and contourlet transform-based de-speckling is provided for both simulated and actual SAR images. It shows that the contourlet methods strongly suppress speckle

while preserving image details and sharpness.