Satellite image segmentation using textural information, contextual information and map knowledge

A technique based on the utilization of both textural and contextual information is proposed for the segmentation of satellite images. Markov random fields are taken as a unified framework for the modeling of satellite images, for the representation of textural as well as contextual information, and, finally, for the formulation of the scene labeling problem. The labeling problem is then solved by a new algorithm based on game strategies. In order to improve its effectiveness, information contained in geographic maps is used for the selection of optimal texture feature descriptors of the images. An adaptive estimation technique is also applied to obtain contextual information. Experimental results show that the technique is very efficient and effective