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

IEEE Transactions on Image Processing

Volumn 5, Issue 7, 1996, Pages 1208-1214

  Zhang, Jun ^a  

^a University of Wisconsin Milwaukee   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; CALCULATIONS; INFORMATION THEORY; MARKOV PROCESSES; MATHEMATICAL MODELS; OPTIMIZATION; RANDOM PROCESSES;

COMPOUND GAUSS MARKOV MODEL; GIBBS-BOGOLIUBOV-FEYNMAN INEQUALITY; MARKOV RANDOM FIELDS; MEAN FIELD THEORY;

IMAGE RECONSTRUCTION;

EID: 0030194148     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/83.502411     Document Type: Article

References (7)

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3. G. Bilbro and W. E. Snyder, "Range image restoration using meanfield annealing," in Advances in Neural Network Information Processing Systems I, D. S. Touretzky, Ed. San Mateo, CA: Morgan Kaufmann, 1988, pp. 594-101.
4. D. Chandler, Introduction to Modern Statistical Mechanics. Oxford, UK: Oxford Univ. Press, 1987.
5. J. Zhang, "The application of the Gibbs-Bogoliubov-Feynman inequality in mean field calculations for Markov random fields," TR EECS Dept., Univ. Wisc., Milwaukee, WI, 1995.
6. F.-C. Jeng and J. W. Woods, "Simulated annealing in compound Gauss-Markov random fields," IEEE Trans. Inform. Theory, vol. 36, pp. 94-107, Jan. 1990.
7. T. Cover and I. Thomas, Elements of Information Theory. New York: Wiley, 1992.