A novel method for computing the partition function of Markov random field images using Monte Carlo simulations

Gerasimos Potamianos, John Goutsias

Abstract: The authors present a new Monte Carlo simulation technique for the estimation of the partition function of a general Markov random field (MRF), which results in unbiased, consistent and asymptotically efficient estimates. This technique gives extremely accurate results, as demonstrated by simulations. Use of more efficient algorithms can boost the performance and accuracy of the method, and yield more reliable estimates.<>