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

Pooja H. M, Dhanushree M. C

Abstract: 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.

Keywords: SAR, RFLICM, Fuzzy Clustering, Imagefusion

How to Cite?: Pooja H. M, Dhanushree M. C, "Change Detection in Synthetic Aperture Radar Image based on Image Fusion and Fuzzy Clustering", Volume 3 Issue 5, May 2014, International Journal of Science and Research (IJSR), Pages: 201-206, https://www.ijsr.net/getabstract.php?paperid=20131649, DOI: https://dx.doi.org/10.21275/20131649

Download Citation: APA | MLA | BibTeX | EndNote | RefMan