A New Method of Remote Sensing Image Segmentation Based on PSO and Isodata

In order to avoid disadvantages of the current algorithms,the Particle Swarm Optimization(PSO) algorithm in the field of artificial intelligence is successfully applied to remote sensing image segmentation.And a new algorithm combined PSO and Isodata is proposed in this paper.This method first changes the color space of the images,then the initial cluster number are determined by the combined algorithm.Finally,the automatic segmentation of remote sensing images is achieved through multiple iterations.Through many experiments of remote sensing images with different spatial resolution,the results show that the new algorithm can determine the initial cluster number adaptively,avoid the local optima of K-means and Isodata algorithms,increase the searching capability of PSO,and the segmentation results are much more close to the actual situation.So it is a new effective algorithm for the segmentation of remote sensing images.