MRF parameter estimation by an accelerated method

Markov random field (MRF) modelling is a popular method for pattern recognition and computer vision and MRF parameter estimation is of particular importance to MRF modelling. In this paper, a new approach based on Metropolis-Hastings algorithm and gradient method is presented to estimate MRF parameters. With properly chosen proposal distribution for Metropolis-Hastings algorithm, the Markov chain constructed by the method converges to stationary distribution quickly and it gives a good estimation result. (C) 2002 Elsevier Science B.V. All rights reserved.Computer Science, Artificial IntelligenceSCI(E)10ARTICLE9-101251-12592