Segmentation of noisy images modelled by Markov random fields with Gibbs distribution

Restoration of noisy images through the use of a Gibbs field model for the image and a Gaussian random field characterization of the corrupting noise is discussed in this paper. Two new algorithms capable of parallel implementation are presented and shown to yield satisfactory restoration of images corrupted by high levels of noise.