Synthetic aperture radar (SAR) image segmentation using a new modified fuzzy c-means algorithm

Abstract

Generally fuzzy c-means algorithm is one proved that very well suited for remote sensing image segmentation, exhibited sensitivity to the initial guess with regard to both speed and stability. But it also showed sensitivity to noise. This paper proposes a fully automatic technique to obtain image clusters. A modified fuzzy c-means classification algorithm is used to provide a fuzzy partition. This method is less sensitive to noise as it filters the image while clustering it, which is based on the consideration of the neighbors as factors the attract pixels into their cluster. The experimental results on JERS-1 synthetic aperture radar (SAR) image demonstrate its potential usefulness.