Change Detection in SAR Images Based on Evolutionary Multi-objective Clustering

SAR images change detection is a challenging task in the field of remote sensing,and it is an urgent problem to keep trade-off between robustness to noise and effectiveness of preserving the details.However,in order to better suppress speckle noise,it is inevitable that most of change detection methods loss image details to some extent.In order to solve this problem,a multi-objective clustering algorithm based on MOEA/D is proposed for change detection in SAR images.The change detection problem is formulated as a multi-objective optimization problem.Two conflicting objectives are constructed and then optimized by the proposed multi-objective clustering algorithm simultaneously.Finally,we obtain a set of change detection maps by the proposed technique.And the users can choose an appropriate one to satisfy their requirements.Experimental results on two SAR images show that the proposed method works well.

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Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-09-01
DOI
https://doi.org/10.11896/jsjkx.230800014
Primary Topic
Food Security and Health in Diverse Populations
Type
article
Field-Weighted Citation Impact
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article

Change Detection in SAR Images Based on Evolutionary Multi-objective Clustering

SHILAP Revista de lepidopterología
Food Security and Health in Diverse Populations
article

Change Detection in SAR Images Based on Evolutionary Multi-objective Clustering

article en

Abstract

SAR images change detection is a challenging task in the field of remote sensing,and it is an urgent problem to keep trade-off between robustness to noise and effectiveness of preserving the details.However,in order to better suppress speckle noise,it is inevitable that most of change detection methods loss image details to some extent.In order to solve this problem,a multi-objective clustering algorithm based on MOEA/D is proposed for change detection in SAR images.The change detection problem is formulated as a multi-objective optimization problem.Two conflicting objectives are constructed and then optimized by the proposed multi-objective clustering algorithm simultaneously.Finally,we obtain a set of change detection maps by the proposed technique.And the users can choose an appropriate one to satisfy their requirements.Experimental results on two SAR images show that the proposed method works well.

SHILAP Revista de lepidopterología
Academy of Military Medical Sciences (CN), PLA Academy of Military Science (CN)
Openalex Percentile: Top 31%
Food Security and Health in Diverse Populations
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Change Detection in SAR Images Based on Evolutionary Multi-objective Clustering · SHILAP Revista de lepidopterología (2024) | TGRS Research Map | TGRS