A general framework for solving image inverse problems is introduced in this paper. The approach is based on Gaussian mixture models, estimated via a computationally efficient MAP-EM algorithm.

This the MATLAB code that was used to produce the figures and tables in Section V of F. Forbes and G. Fort, Combining Monte Carlo and mean-field like methods for inference in Hidden Markov Random Fields, Accepted for publication in IEEE Trans. on