A novel pseudo-likelihood equation for Potts MRF model parameter estimation in image analysis

This paper presents a novel pseudo-likelihood equation for the estimation of the Potts MRF model parameter on second-order neighborhood systems, allowing the modeling of less restrictive contextual systems in a large number of MRF applications in a computationally feasible way. We propose a hypothesis testing approach to validate the obtained results. The test statistic together with the p-values, calculated through our approximation for the asymptotic variance of the derived maximum pseudo-likelihood estimator, provide a complete framework for quantitative analysis in MRF parameter estimation.