A Clustering Approach for Change Detection in SAR Images

Konferenz: EUSAR 2012 - 9th European Conference on Synthetic Aperture Radar
23.04.2012 - 26.04.2012 in Nuremberg, Germany

Tagungsband: EUSAR 2012

Seiten: 4Sprache: EnglischTyp: PDF

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Luo, Fang; Yang, Wen; Wu, Qiong; Yan, Wei (School of Electronic Information & LIESMARS, Wuhan University, China)

This paper presents a new approach for change detection in SAR images based on clustering method. Classic change detection methods use a hard threshold to divide the difference map into two classes: change and unchanged, which has a disadvantage that some weak changed regions are often undetected. Unlike those methods, our proposed method use expectation maximization with graph cut optimization to cluster the difference map into three classes: strong changed areas, weak changed areas and unchanged areas. The experimental results on real SAR images show that our approach obtains a higher detection rate than the previous ones.