%0 Conference Proceedings
%T Estimation of non-homogeneous Potts-Strauss MRF model parameters on higher-order neighborhood systems by maximum pseudo-likelihood
%8 Oct. 7-10, 2007
%A Levada, Alexandre Luis Magalhães,
%A Mascarenhas, Nelson Delfino d'Ávila,
%@affiliation Universidade de São Paulo
%@affiliation Universidade Federal de São Carlos
%E Gonçalves, Luiz,
%E Wu, Shin Ting,
%B Brazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
%C Belo Horizonte
%I Sociedade Brasileira de Computação
%J Porto Alegre
%K Markov Random Fields, Potts-Strauss model, maximum pseudo-likelihood.
%X This paper addresses the problem of maximum pseudo-likelihood estimation of the non-homogeneous Potts-Strauss image model parameters using higher-order non-causal neighborhood systems in a computationally efficient way. The motivation is the development of a new methodology for contextual classification that uses combination of sub-optimal MRF algorithms for multispectral image classification, which requires accurate parameters estimation. The results show that the method is consistent with real image data and in the presence of random noise.