An adaptive segmentation algorithm is proposed based on local spatial adaptive Markov random field(MRF)
model to solve the problem that the Pairwise MRF model is insufficient to capture the rich statistics features of images by a
single set of fixed parameters. Firstly, the proposed algorithm constructs the local spatial adaptive model based on Pairwise
MRF. For every local region, the local prior is adaptively estimated. Then loopy belief propagation(LBP) algorithm based
on the local region belief convergence is used to maximize the global posterior probability of the adaptive MRF model.
Experimental results show that the proposed algorithm can provide a better segmentation result.