احمد کشاورز

Remote sensing images include a large amount of information. In this paper, we present a fuzzy clustering method for these images, which is a combination of Gustafson-Kessel clustering algorithms and minimum cluster volume. The methodology is that a fuzzy clustering is first performed on the image and the result is minimized in the cluster volume algorithm to minimize the total volume of each cluster. Then, a fuzzy clustering is repeated on the result and, if the desired criterion is met, each cluster is split into two clusters. This process continues until the termination condition is reached. The proposed algorithm is implemented on the AVIRIS images. The results show that the proposed algorithm provides better clustering compared to common fuzzy clustering algorithms of these images.