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Sensors 2018, 18(7), 2215; https://doi.org/10.3390/s18072215

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

1
School of Geosciences and Info-Physics, Central South University, Changsha 410083, China
2
Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring, Ministry of Education, Central South University, Changsha 410083, China
*
Author to whom correspondence should be addressed.
Received: 13 June 2018 / Revised: 4 July 2018 / Accepted: 7 July 2018 / Published: 10 July 2018
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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. View Full-Text
Keywords: polarimetric synthetic aperture radar (PolSAR); polarimetric likelihood ratio test (PolLRT); region growing (RG); shape-adaptive (SA) patches matching; nonlocal means (NLM) polarimetric synthetic aperture radar (PolSAR); polarimetric likelihood ratio test (PolLRT); region growing (RG); shape-adaptive (SA) patches matching; nonlocal means (NLM)
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Shen, P.; Wang, C.; Gao, H.; Zhu, J. An Adaptive Nonlocal Mean Filter for PolSAR Data with Shape-Adaptive Patches Matching. Sensors 2018, 18, 2215.

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