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 pro-posed 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.
SAR imagesChange detectionSpeckle noiseImage detailsMulti-objective optimizationClustering
万方数据
维普
