A MRF based approach to color image restoration

In this paper, a Markov Random Field (MRF)-based method is presented. MRF methods are based on a probabilistic representation of a image processing problem; the problem is represented as the maximization of a probability measure computed starting from input data for all possible solutions. The optimization process is often computationally expensive. The coupled problem of restoring and extracting edges from an image is here considered. An extension to the color case of the deterministic mean-field annealing method presented in [1] is presented. The main advantage of this approach is its capability of obtaining a sub-optimum solution in a faster way with respect to optimal stochastic methods (e.g., Simulated Annealing).