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基于广义似然比的小波域SAR图像相干斑抑制算法

Generalized Likelihood Ratio Based SAR Image Speckle Suppression Algorithm in Wavelet Domain
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摘要 在联合检测与估计理论框架下推导出了Bayes萎缩函数表达式,并提出了一种基于广义似然比的小波域SAR图像去斑算法.该算法对含斑SAR图像直接做冗余小波变换,求出小波系数所对应的二值掩模;对相干斑噪声和有用信号的似然条件概率分别建模为尺度指数分布和Gamma分布,根据二值掩模信息,采用最大似然估计得到两种模型的参数并计算似然条件概率比.实验结果表明:文中所给算法在有效滤除斑点噪声的同时,也较好地保持了图像的细节信息,在对人工加斑图像和多幅实际SAR图像的处理中获得了令人满意的结果. A Bayes shrinkage formula is derived under the framework of joint detection and estimation theory,and a wavelet SAR image despeckling algorithm is realized based on generalized likelihood ratio. Firstly,redundant wavelet transform is performed directly to the original speckled SAR images,and binary mask is obtained for each wavelet coefficient. We use scale exponential distribution and Gamma distribution,respectively,to model the likelihood conditional probability of speckle noise and useful signal. According to the mask,the parameters of the two modes are estimated by maximum likelihood estimation method,and thus the likelihood conditional probability ratio is calculated. Experiment results show that the proposed method can effectively filter the speckle noise,and at the same time preserve the image details as possible. Satisfactory results are achieved on both synthetically speckled images and real SAR images.
作者 侯建华 刘欣达 陈稳 陈少波
机构地区 中南民族大学电子信息工程学院
出处 《中南民族大学学报（自然科学版）》 CAS 北大核心 2015年第1期93-98,共6页 Journal of South-Central University for Nationalities：Natural Science Edition
基金 国家自然科学基金资助项目(61141010 61201448) 湖北省自然科学基金资助项目(2012FFA113)
关键词 联合检测与估计 SAR图像去斑 小波变换 广义似然比 joint detection and estimation SAR image despeckling wavelet transform generalized likelihood ratio
分类号 TN911.73 [电子电信—通信与信息系统]
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参考文献15

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二级参考文献14

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中南民族大学学报（自然科学版）
2015年 第1期

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