基于同质像素预选择的极化SAR图像非局部均值滤波

杨学志; 陈靖; 周芳; 郎文辉; 郑鑫; 李国强

doi:10.11999/JEIT150314

基于同质像素预选择的极化SAR图像非局部均值滤波

doi: 10.11999/JEIT150314

2.
(合肥工业大学计算机与信息学院合肥 230009) ②(光电控制技术重点实验室洛阳 471009)

基金项目:

国家自然科学基金(61371154, 41076120, 61271381, 61102154)，光电控制技术重点实验室和航空科学基金联合资助项目(201301P4007)和中央高校基本科研业务费专项(2012HGCX0001)

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出版历程
- 收稿日期: 2015-03-17
- 修回日期: 2015-08-28
- 刊出日期: 2015-12-19

Polarimetric SAR Image Despeckling Using Non Local Means Filter Based on Homogeneous Pixels Preselection

2.
(School of Computer and Information, Hefei University of Technology, Hefei 230009, China)

Funds:

The National Natural Science Foundation of China (61371154, 41076120, 61271381, 61102154)

摘要

摘要: 该文针对在极化合成孔径雷达(PolSAR)图像相干斑抑制过程中结构特征和极化散射特性保持的难题，提出一种基于同质像素预选择的非局部均值滤波算法(NLM-HPP)。该算法结合像素统计特性和极化散射机制选择滤波同质像素，并引入结构损失函数提高非局部均值(NLM)算法中像素间相似性度量的准确性，最后用改进的相似性度量对同质像素的协方差矩阵进行加权平均，实现对PolSAR图像的相干斑抑制。对真实PolSAR数据进行的实验结果表明，与现有的Refined Lee滤波、基于散射模型的滤波方法和两种非局部均值滤波相比，此方法在有效滤除相干斑点的同时能更好地保持PolSAR图像的结构信息和极化信息。
- 极化合成孔径雷达 /
- 非局部均值 /
- 结构保持 /
- 极化信息 /
- 同质像素预选择
Abstract: A Non Local Means (NLM) filtering based on Homogeneous Pixels Preselection (NLM-HPP) is proposed to solve the problem of preserving structural feature and polarimetric scattering properties in speckle reduction of Polarimetric SAR (PolSAR) images. Firstly, this method combines statistical property and polarimetric scattering mechanism to select homogeneous pixels in the filtering process. Secondly, the loss function of structure is introduced to improve the accuracy of similarity measure between pixels in NLM method. Finally, it averages the covariance matrices of homogeneous pixels with the weights according to the refined similarity measure, inducing efficient reduction of the speckle in PolSAR images. The implementation results on real PolSAR images, compared with the Refined Lee filter, Scattering-Model-Based speckle filter and two kinds of Non Local Means filter, demonstrate that the proposed method can reduce speckle effectively, and further retain structural information and polarimetric information in PolSAR images.
- Polarimetric SAR (PolSAR) /
- Non Local Means (NLM) /
- Structure preserving /
- Polarimetric information /
- Homogeneous pixels preselection

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参考文献(25)

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