Statistical approach for Segmentation of satellite image with Markov random field Model

Satellite imagery is one of the wide areas in segmentation. They are used for Analysis of the different elements of the landscapes such as cropland, bare land, forests, flooded areas, assists in vegetation, disease detection, facilitates monitoring of deforestation and desertification, as well as the evolution of infrastructure in inhabited areas or the sea ice. In this paper, we propose an image segmentation method based on Markov random field model and Gibbs distributions, we introduce iterative algorithm process to minimize an energy function.