Change detection in SAR images by means of grouping connected regions using clone selection algorithm
- 1 January 2011
- journal article
- Published by Institution of Engineering and Technology (IET) in Electronics Letters
- Vol. 47 (5), 338-339
- https://doi.org/10.1049/el.2010.2596
Abstract
Most of the change detection techniques for SAR images based on the analysis of the difference image always generate the result map at the pixel level, which leads to a noisy change detection map, with holes in connected components and jagged boundaries. To attack this problem, a novel technique to generate the result at the region level is proposed, which considers each connected region as an agent and then gives the optimal label combination for all agents through the clone selection algorithm and a new fitness function. The region oriented method can avoid the above problem and improve the change detection performance. Experimental results on the real Radarsat SAR dataset validate the effectiveness of the method on both the quantitative and subjective aspects.Keywords
This publication has 6 references indexed in Scilit:
- Change Detection in Satellite Images Using a Genetic Algorithm ApproachIEEE Geoscience and Remote Sensing Letters, 2010
- Markovian Fusion Approach to Robust Unsupervised Change Detection in Remotely Sensed ImageryIEEE Geoscience and Remote Sensing Letters, 2006
- Image segmentation by histogram thresholding using hierarchical cluster analysisPattern Recognition Letters, 2006
- A detail-preserving scale-driven approach to change detection in multitemporal SAR imagesIEEE Transactions on Geoscience and Remote Sensing, 2005
- Image change detection algorithms: a systematic surveyIEEE Transactions on Image Processing, 2005
- Automatic analysis of the difference image for unsupervised change detectionIEEE Transactions on Geoscience and Remote Sensing, 2000