Non-local mean despeckling algorithm based on edge strength map and region division for SAR image

In order to reduce the multiplicative speckle noise of synthetic aperture radar(SAR) image, an improved non-local mean (NLM) algorithm is proposed in this paper. Firstly, the coefficient of variation (CV) was used to estimate the SAR image region division threshold, and estimate area division factor...

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Published inXi'An Gongcheng Daxue Xuebao Vol. 35; no. 1; pp. 75 - 80
Main Authors Zijin FENG, Lei ZHU, Fei GAO
Format Journal Article
LanguageChinese
Published Editorial Office of Journal of XPU 01.02.2021
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ISSN1674-649X
DOI10.13338/j.issn.1674-649x.2021.01.012

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Abstract In order to reduce the multiplicative speckle noise of synthetic aperture radar(SAR) image, an improved non-local mean (NLM) algorithm is proposed in this paper. Firstly, the coefficient of variation (CV) was used to estimate the SAR image region division threshold, and estimate area division factor based on threshold. Thus, the SAR image wasdivided into texture area and homogeneous area by area division factor. Then, similarity windows of different scales were used to estimate the ESM corresponding to pixels in different regions, and the ESM matrix of each pixel in the search window under the similarity window and the ESM matrix of the center pixel were selected further. Moreover, the two-norm of the ratio of the two corresponding elements were used to construct the similarity measurement parameter that adapts to the multiplicative noise, filter value was obtained by combining the similarity parameter with the adaptive decay factor dominated by CV. Finally, the non-local average weighted filtering of the SAR
AbstractList In order to reduce the multiplicative speckle noise of synthetic aperture radar(SAR) image, an improved non-local mean (NLM) algorithm is proposed in this paper. Firstly, the coefficient of variation (CV) was used to estimate the SAR image region division threshold, and estimate area division factor based on threshold. Thus, the SAR image wasdivided into texture area and homogeneous area by area division factor. Then, similarity windows of different scales were used to estimate the ESM corresponding to pixels in different regions, and the ESM matrix of each pixel in the search window under the similarity window and the ESM matrix of the center pixel were selected further. Moreover, the two-norm of the ratio of the two corresponding elements were used to construct the similarity measurement parameter that adapts to the multiplicative noise, filter value was obtained by combining the similarity parameter with the adaptive decay factor dominated by CV. Finally, the non-local average weighted filtering of the SAR
Author Fei GAO
Lei ZHU
Zijin FENG
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  organization: School of Electronics and Information, Xi’an Polytechnic University, Xi’an 710048, China
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Snippet In order to reduce the multiplicative speckle noise of synthetic aperture radar(SAR) image, an improved non-local mean (NLM) algorithm is proposed in this...
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StartPage 75
SubjectTerms edge strength map
non-local mean filtering
region division
speckle noise
synthetic aperture radar image
Title Non-local mean despeckling algorithm based on edge strength map and region division for SAR image
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