Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (9): 140-146.doi: 10.11896/jsjkx.230800014

• Computer Graphics & Multimedia • Previous Articles     Next Articles

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

ZHOU Yu1, YANG Junling2, DANG Kelin1   

  1. 1 School of Electronic Engineering,Xidian University,Xi'an 710071,China
    2 Military Science Information Research Center,Academy of Military Sciences,Beijing 100142,China
  • Received:2023-08-03 Revised:2024-07-01 Online:2024-09-15 Published:2024-09-10
  • About author:ZHOU Yu,born in 1983,Ph.D.His main research interests include machine learning and evolutionary computation.
    YANG Junling,born in 1975,Ph.D.His main research interest is national defense artificial intelligence.

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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.

Key words: SAR images, Change detection, Speckle noise, Image details, Multi-objective optimization, Clustering

CLC Number: 

  • TP391.4
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