Synthetic Aperture Radar Image Change Detection Using Fuzzy C-Means Clustering Algorithm

Abstract: This paper presents a novel approach to change detection in synthetic aperture radar (SAR) images based on image fusion and fuzzy clustering. The proposed approach use mean-ratio image and log-ratio image to generate a difference image by image fusion technique. In order to enhance the information of changed regions and background information in the difference image is based on the wavelet fusion rule. A reformulated fuzzy local c means clustering algorithm is used for differentiating changed and unchanged regions in the fused image, which is insensitive to noise and reduce the effect of speckle noise. By this method we get a better performance and lower error than the pre-existence.

Keywords: Image fusion, clustering, fuzzy c-means algorithm (FCM), Synthetic Aperture Radar (SAR), image change detection.