摘要 该文提出一种基于结构相似性指数(SSIM)的非局部均值(Non Local means, NL-means)滤波的合成孔径雷达(SAR)图像相干斑噪声抑制新方法。该方法用SSIM改进NL-means算法中小块相似性的度量，能利用结构信息来进行相干斑抑制。通过在真实SAR图像上的实验表明，与GammaMAP滤波、CHMT算法、BLS-GSM算法、NL-means滤波相比，此方法在有效去除相干斑噪声的同时能更好地保持边缘结构信息。
Abstract：This paper proposes a new speckle reduction algorithm for Synthetic Aperture Radar (SAR) images. It is based on the Non Local (NL) means filter and improved by Structural SIMilarity (SSIM). Structure information is introduced into the despeckling method by measuring the similarity between small patches with SSIM. Some experiments on real SAR images, comparing with GammaMAP filter, Contourlet Hidden Markov Tree (CHMT) method, Bayes Least Squares-Gaussian Scale Mixtures (BLS-GSM) method and NL-means filter, demonstrate that the proposed algorithm is able to reduce efficiently speckle while retain edges and structures well.
易子麟, 尹东, 胡安洲, 张荣. 基于非局部均值滤波的SAR图像去噪[J]. 电子与信息学报, 2012, 34(4): 950-955.
Yi Zi-Lin, Yin Dong, Hu An-Zhou, Zhang Rong. SAR Image Despeckling Based on Non-local Means Filter. , 2012, 34(4): 950-955.
2012, Vol. 34 
