Analytical method for MGRF Potts model parameter estimation

This paper proposes a new analytical method for estimating parameters of a homogeneous isotropic Potts model with an asymmetric Gibbs potential function. The model is generalized by including both pairwise and triple cliques. The maximum likelihood estimates of the cliques potentials are obtained by a further elaboration of the approximate analytical estimator proposed in [8]. Experiments with synthetic textures have shown that our potential estimates are more accurate and practicable than their counterparts obtained with classical methods.

• Type: Conference
• Year: 2008
• Where: ICPR
• Authors: Asem M. Ali, Aly A. Farag, Georgy L. Gimel'farb
• Keywords: Computer Vision, Gibbs Potential Function, Homogeneous Isotropic Potts, ICPR 2008, Maximum Likelihood Estimates