DocumentCode
1987747
Title
A novel method for computing the partition function of Markov random field images using Monte Carlo simulations
Author
Potamianos, Gerasimos ; Goutsias, John
Author_Institution
Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
fYear
1991
fDate
14-17 Apr 1991
Firstpage
2325
Abstract
The authors present a new Monte Carlo simulation technique for the estimation of the partition function of a general Markov random field (MRF), which results in unbiased, consistent and asymptotically efficient estimates. This technique gives extremely accurate results, as demonstrated by simulations. Use of more efficient algorithms can boost the performance and accuracy of the method, and yield more reliable estimates
Keywords
Markov processes; Monte Carlo methods; picture processing; Markov random field images; Monte Carlo simulations; partition function; Closed-form solution; Equations; Image analysis; Laboratories; Lattices; Markov random fields; Maximum likelihood estimation; Monte Carlo methods; Probability distribution; Samarium;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location
Toronto, Ont.
ISSN
1520-6149
Print_ISBN
0-7803-0003-3
Type
conf
DOI
10.1109/ICASSP.1991.150772
Filename
150772
Link To Document