A Grey Wolf Optimizer Based Automatic Clustering Algorithm for Satellite Image Segmentation

Grey Wolf Optimizer has recently emerged as an efficient meta-heuristic optimization technique. It has good capability in exploitation for unimodal problems, superior exploration ability for multimodal problems, and also works fine for composite functions avoiding local minimas. This paper proposes an application of Grey Wolf Optimizer (GWO) algorithm for satellite image segmentation. The original GWO has been suitably modified to work as an automatic clustering algorithm. This algorithm has been applied on two satellite images. It is computationally efficient and its accuracy is superior in many cases in terms of Davies-Bouldin (DB) index, average inter-cluster distance and average intra-cluster distance. (C) 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 7th International Conference on Advances in Computing & Communications.