On the Selection of Markov Random Field Texture Models
نویسنده
چکیده
The problem of selecting pair-potentials of finite range for Gibbs random fields is considered as an important step in modelling multi-textured images. In a decision theoretic set-up, the Bayesian procedure is approximated by using Laplace's method for asymptotic expansion of integrals. Certain frequentist properties of the selection procedure are investigated. In particular, its consistency is justified regardless of phase transition of the Gibbs random fields.
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