The application of the Gibbs-Bogoliubov-Feynman inequality in mean field calculations for Markov random fields

  • Authors:

  • Jun Zhang

  • Affiliations:

  • Dept. of Electr. Eng. & Comput. Sci., Wisconsin Univ., Milwaukee, WI

  • Venue:
  • IEEE Transactions on Image Processing
  • Year:
  • 1996

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Abstract

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