A Novel Fuzzy Probabilistic Clustering Algorithm for Satellite Image Segmentation

Satellite Image Segmentation is a task widely investigate since we can extract and analyze information of an image. In satellite image, the information of each one of the bands must be considered. We propose a new method based on the New Fuzzy Centroid Model and includes spatial information. Furthermore, we use the occurrence of each intensity value in a particular band and the Gaussian function in order to compute the degree of contribution of pixels in the neighborhood. By incorporating spatial information (global and local), we improve the clustering process and consequently, a better segmentation is obtained. This paper reports preliminary results of experiments that show that the proposed algorithm performs accurately on a real data set. For the evaluation of the algorithm, different cluster validity indexes are employed.