Stochastic relaxations and em algorithms for markov random fields

Abstract

This paper presents a simulation study of block (one line or two lines of pixels) updating for Markov random fields. Point and line relaxation methods are compared. Some pseudo-likelihoods, based on the conditional density of a block of pixels, are used together with modified EM algorithms to estimate parameters from noisy images.

Keywords:

• EM algorithm
• Gibbs chain
• Markov random field
• Maximum pseudo-likelihood estimation
• Maximum asymptotic-likelihood estimation
• Neighbourhood system
• Restoration