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基于形状自适应斑块匹配的极化合成孔径雷达数据自适应非局部均值滤波

An Adaptive Nonlocal Mean Filter for PolSAR Data with Shape-Adaptive Patches Matching.

机构信息

School of Geosciences and Info-Physics, Central South University, Changsha 410083, China.

Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha 410083, China.

出版信息

Sensors (Basel). 2018 Jul 10;18(7):2215. doi: 10.3390/s18072215.

DOI:10.3390/s18072215
PMID:29996522
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6069051/
Abstract

The traditional nonlocal filters for polarimetric synthetic aperture radar (PolSAR) images are based on square patches matching to obtain homogeneous pixels in a large search window. However, it is still difficult for the regular patches to work well in the complex textured areas, even when the patch size has a small enough setting (e.g., 3 × 3 windows). Therefore, this paper proposes an adaptive nonlocal mean filter with shape-adaptive patches matching (ANLM) for PolSAR images. Mainly, the shape-adaptive (SA) matching patches are constructed by combining the polarimetric likelihood ratio test for coherency matrices (PolLRT-CM) and the region growing (RG), which is called PolLRT-CMRG. It is used to distinguish the homogeneous and heterogeneous pixels in textured areas effectively. Then, to enhance the filtering effect, it is necessary to take the adaptive threshold selection of similarity test (Simi-Test) into consideration. The simulated, low spatial resolution SAR580-Convair and high spatial resolution ESAR PolSAR image datasets are selected for experiments. We make a detailed quantitative and qualitative analysis for the filtered results. The experimental results have demonstrated that the proposed ANLM filter has better performance in speckle suppression and detail preservation than that of the traditional local and nonlocal filters.

摘要

传统的极化合成孔径雷达(PolSAR)图像的非局部滤波器基于方形补丁匹配,以在大搜索窗口中获得同质像素。然而,即使在补丁尺寸设置足够小(例如 3x3 窗口)的情况下,规则补丁在复杂纹理区域中仍然难以很好地工作。因此,本文提出了一种用于 PolSAR 图像的具有形状自适应补丁匹配的自适应非局部均值滤波器(ANLM)。主要地,通过结合相干矩阵的极化似然比检验(PolLRT-CM)和区域生长(RG)来构建形状自适应(SA)匹配补丁,称为 PolLRT-CMRG。它用于有效地区分纹理区域中的同质和异质像素。然后,为了增强滤波效果,需要考虑自适应相似性测试(Simi-Test)的阈值选择。选择了模拟的低空间分辨率 SAR580-Convair 和高空间分辨率 ESAR PolSAR 图像数据集进行实验。我们对滤波结果进行了详细的定量和定性分析。实验结果表明,与传统的局部和非局部滤波器相比,所提出的 ANLM 滤波器在抑制斑点和保持细节方面具有更好的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/d78ac6297ca0/sensors-18-02215-g014.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/b5e654f4e77b/sensors-18-02215-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/a13b4c0875b7/sensors-18-02215-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/3ef56fd4acdf/sensors-18-02215-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/b725412a82ee/sensors-18-02215-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/6efbef402667/sensors-18-02215-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/13e4f09abae2/sensors-18-02215-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/43476f70e436/sensors-18-02215-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/d3601b330187/sensors-18-02215-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/d432d90db48c/sensors-18-02215-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/d78ac6297ca0/sensors-18-02215-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/efa3b7366a3a/sensors-18-02215-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/c6336c3450a8/sensors-18-02215-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/d81b283eddd5/sensors-18-02215-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/993d3503092e/sensors-18-02215-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/b5e654f4e77b/sensors-18-02215-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/a13b4c0875b7/sensors-18-02215-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/3ef56fd4acdf/sensors-18-02215-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/b725412a82ee/sensors-18-02215-g008a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/6efbef402667/sensors-18-02215-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/13e4f09abae2/sensors-18-02215-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/43476f70e436/sensors-18-02215-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/d3601b330187/sensors-18-02215-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/d432d90db48c/sensors-18-02215-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddf0/6069051/d78ac6297ca0/sensors-18-02215-g014.jpg

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