基于非局部均值滤波的结构保持相干斑噪声抑制方法

摘要

This paper proposes a nonlocal means filter-based speckle reduction algorithm for synthetic aperture radar (SAR) images. In contrast to traditional methods, the proposed method is capable of discerning pixels of same structural features by exploiting similarity between image patches, leading to efficient reduction of structural information in despeckling. In terms of characteristics of similarity of various structural primitives, a two-stage nonlocal means filtering is used for alleviating the impact of noise on structural similarity measures, and hence improve the despeckling performance. The proposed method has been evaluated on simulated SAR images with varying levels of speckle noise and a real SAR image. Compared to the traditional Lee filter, enhanced Lee filter and the speckle reducing anisotropic diffusion (SRAD) , the proposed method substantially improves the despeckling performance especially on the preservation of structure information.%提出了一种基于非局部均值滤波的合成孔径雷达(SAR)图像相干斑噪声抑制新方法.与传统方法相比,该方法通过利用SAR图像块之间的相似性来辨别具有相同结构属性的像素,从而实现在抑制相干斑噪声的同时有效减少图像结构信息的损失.针对SAR图像中各种结构基元相似性的特点,进一步采用两级非局部均值滤波,来削弱相干斑噪声对结构相似性度量的影响,提高去噪性能.通过采用添加不同程度相干斑噪声的合成sAR图像和真实SAR图像对提出的方法进行评价,实验结果表明,与传统的Lee滤波方法,增强的Lee滤波方法以及各向异性扩散相干斑抑制方法相比,提出的方法在相干斑噪声抑制尤其是结构信息保持性能上有显著提高.