3维块匹配小波变换的极化SAR非局部均值滤波

发布时间：2018-03-07 09:37

本文选题：极化SAR　切入点：相干斑抑制　出处：《遥感学报》2017年02期 　论文类型：期刊论文

【摘要】：极化合成孔径雷达(SAR)图像受相干斑噪声的影响,难以很好地保持结构特性,针对这个问题提出了一种采用3维块匹配小波变换的非局部均值滤波算法NL-3DWT(Nonlocal Filter based on 3-D Patch Matching Wavelet Transform)。该算法使用块匹配的3维非抽样小波变换对极化总功率图进行预滤波,在此基础上使用边界对齐窗提取结构相似像素,同时使用Sigma范围选择极化SAR数据的散射相似像素,共同构成相似像素集合;构建结构保持权重函数增大图像结构信息在块相似性度量时的权重,最终实现极化SAR图像结构保持的相干斑抑制。该算法增强了图像结构特征的表达,提高了结构相似像素选择的准确性,机载极化SAR数据实验结果表明,NL-3DWT算法能够在抑制相干斑噪声的同时,更有效地保持极化SAR图像的结构特性和极化散射特性。
[Abstract]:Polarimetric synthetic Aperture Radar (SAR) images are hard to maintain structural characteristics due to speckle noise. To solve this problem, a non-local mean filter algorithm, NL-3DWT(Nonlocal Filter based on 3-D Patch Matching Wavelet transform, is proposed, which uses block-matched 3D non-sampling wavelet transform to pre-filter the total polarimetric power map. On this basis, we use the boundary alignment window to extract the similar pixels with similar structure, and use the Sigma range to select the scattered similar pixels of the polarized SAR data, so as to form a set of similar pixels. A structure-preserving weight function is constructed to increase the weight of image structure information in block similarity measurement, and finally the speckle suppression of polarimetric SAR image structure retention is realized. This algorithm enhances the expression of image structure features. The experimental results of airborne polarimetric SAR data show that the NL-3DWT algorithm can suppress speckle noise and maintain the structure and polarization scattering characteristics of polarimetric SAR images more effectively.
【作者单位】：合肥工业大学计算机与信息学院;
【基金】：国家自然科学基金(编号:61371154,61271381,61503111) 安徽省自然科学基金(编号:1608085QF142) 中央高校基本科研业务费专项资金资助(编号:2015HGBZ0106,2015HGQC0005) 国家博士后科学基金(编号:2016M592045)~~
【分类号】：TN957.52

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