基于低秩分解和改进的非局部平均的SAR图像相干斑抑制  

A SAR Image Despeckling Method Based on Low-rank Decomposition and Improved Non-local Means

作　　者：沈荻帆 张育 任佳[1] Shen Difan;Zhang Yu;Ren Jia(School of Information and Communication, Hainan University, Haikou, Hainan 570228,China)

机构地区：[1]海南大学信息与通信学院,海南海口570228

出　　处：《信号处理》2020年第3期463-470,共8页Journal of Signal Processing

基　　金：海南省自然科学基金面上项目(618MS029)。

摘　　要：为抑制合成孔径雷达(SAR)图像成像过程中形成的相干斑噪声,提出了一种基于低秩分解和改进的非局部平均的SAR图像相干斑去噪方法。首先将SAR图像进行对数处理,将乘性噪声转换为加性噪声;然后利用低秩稀疏分解将对数图像分解成低秩图像部分和稀疏图像部分;接着对含噪严重的稀疏图像部分分析其结构张量,生成非局部平均滤波所需的衰减因子,进行改进的非局部平均滤波去噪;最后再做图像合成,经指数变换得到去噪后的SAR图像。实验结果表明,该方法经视觉评价、边缘保持指数(EPI)和等效视数(ENL)等方面评测,具有较好的抑制噪声和保持边缘及纹理细节的能力。In order to suppress the speckle noise generated in the imaging process of synthetic aperture radar(SAR)images,a novel SAR despeckling method based on low-rank decomposition and improved non-local means was proposed.Firstly,the logarithmic processing of SAR image was carried out to convert multiplicative noise into additive noise.Then the logarithmic image was divided into low-rank image part and sparse image part with low-rank and sparse decomposition theory.After that the structure tensor of the sparse image with serious noise was analyzed to generate the attenuation factor required by the non-local means filtering,and the improved non-local average filtering was carried out to remove noise.Finally,the images were combined and the despeckling SAR image was obtained by exponential transformation.The experimental results demonstrate that,the proposed method has good ability of suppressing noise and keeping the detail better after visual evaluation,EPI and ENL.

关 键 词：合成孔径雷达 低秩分解 非局部平均 等效视数 边缘保持指数 相干斑抑制 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]