Approximate maximum likelihood hyperparameter estimation for Gibbs priors

Volume: 6, Issue: 6, Pages: 844 - 861
Published: Jun 1, 1997
Abstract
The parameters of the prior, the hyperparameters, play an important role in Bayesian image estimation. Of particular importance for the case of Gibbs priors is the global hyperparameter, /spl beta/, which multiplies the Hamiltonian. Here we consider maximum likelihood (ML) estimation of /spl beta/ from incomplete data, i.e., problems in which the image, which is drawn from a Gibbs prior, is observed indirectly through some degradation or...
Paper Details
Title
Approximate maximum likelihood hyperparameter estimation for Gibbs priors
Published Date
Jun 1, 1997
Volume
6
Issue
6
Pages
844 - 861
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