An adaptive seed point selection technique for segmentation of polarimetric synthetic aperture radar images

Abstract

The performance of the most popular unsupervised clustering algorithm, k-means depends on the initial seed points. This paper proposes a mode based adaptive seed selection algorithm, which is used to improve the performance of Wishart segmentation for the segmentation of polarimetric synthetic aperture radar images.