Change Detection in Synthetic Aperture Radar Image based on Image Fusion and Fuzzy Clustering

Change detection approach for synthetic aperture radar (SAR) images based on an image fusion strategy and a fuzzy clustering algorithm. The image fusion technique is introduced to generate a difference image by using complementary information from a mean-ratio image and a log-ratio image. In order to restrain the background information and enhance the information of changed regions in the fused difference image. A reformulated fuzzy local-information C-means (RFLICM) clustering algorithm is proposed for classifying changed and unchanged regions in the fused difference image. It incorporates the information about spatial context in a novel fuzzy way for the purpose of enhancing the changed information and of reducing the effect of speckle noise.