The application of the Gibbs-Bogoliubov-Feynman inequality in mean field calculations for Markov random fields.
The Gibbs-Bogoliubov-Feynman (GBF) inequality of statistical mechanics is adopted, with an information-theoretic interpretation, as a general optimization framework for deriving and examining various mean field approximations for Markov random fields (MRF's). The efficacy of this approach is demonstrated through the compound Gauss-Markov (CGM) model, comparisons between different mean field approximations, and experimental results in image restoration.
Zhang
J
J
Dept. of Electr. Eng. and Comput. Sci., Wisconsin Univ., Milwaukee, WI.