Parameter estimation in Markov random field image modeling with imperfect observations: a comparative study

Authors:
M. V. Ibáñez;A. Simó
Affiliations:
Department of Mathematics, Universitat Jaume I, Campus de Riu Sec. 12071 Castellón, Spain;Department of Mathematics, Universitat Jaume I, Campus de Riu Sec. 12071 Castellón, Spain
Venue:
Pattern Recognition Letters
Year:
2003

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Abstract

Many algorithms in unsupervised image analysis are based on Markov random fields, and parameter estimation plays an important role. Two difficulties are usually present: the presence of unobserved data and the fact that the normalizing constant of the model is unknown. In this paper we show the application to this context of a parameter estimation method which is popular in the point process context. We shortly review other related methods and finally we do a simulation study in order to compare them.