  A review of Bayesian restoration of digital images based on Monte Carlo
techniques is presented. The topics covered include Likelihood, Prior and
Posterior distributions, Poisson, Binay symmetric channel, and Gaussian channel
models of Likelihood distribution,Ising and Potts spin models of Prior
distribution, restoration of an image through Posterior maximization,
statistical estimation of a true image from Posterior ensembles, Markov Chain
Monte Carlo methods and cluster algorithms.
