Nonlocal means filter for polarimetric SAR images based on fusion distance
In the field of polarimetric synthetic aperture radar(SAR)image denoising,the common nonlocal means(NLM)filter only relies on the statistical distance between pixels to measure the similarity and ignores the spatial information of them.This study combines the statistical characteristics of polarimetric SAR data and image spatial features as similarity measures between pixels,and proposes a method for calculating adjacent window weights using fusion distance,which names NLM filter based on fusion distance(FD-NLM).The introduction of fusion distance enables the filter to comprehensively evaluate the similarity between pixels,thereby obtaining more appropriate pixel weights.In addition,this method also employs the coefficient of variation(CV)to evaluate the weight of neighborhood windows,and using this parameter to control the filtering degree.The experimental results on multiple polarimetric SAR images show that the proposed filter can effectively suppress speckle noise while retaining relatively complete image edge information and polarization scattering characteristics.
polarimetric synthetic aperture radar(SAR)nonlocal means(NLM)filtersimilarity measurecoefficient of variation(CV)
万方数据
维普
