Through defining the new potential functions

a SAR image segmentation method is proposed based on Bayes belief propagation and regional MRF model.Considering the rich texture information of SAR images

texture features are extracted from the watershed over-segmented regions

and then an MRF model is defined over the region adjacency graph of the initially segmented regions.Features of each small region are denoted by the texture features

the average and variance of the gray level of all the pixels in each region.The associated potential function is defined by the initial segmentation obtained from FCM clustering with the region.The features of the small regions are introduced to the interaction potential function.The new interaction potential function can effectively protect edge and promote regional consistency at the same time.In the experiments

the proposed algorithm is compared with other MRF image segmentation algorithms using real SAR images.The experimental results show that the proposed method is more effective for SAR image segmentation.