DocumentCode :
2479962
Title :
Analytical method for MGRF Potts model parameter estimation
Author :
Ali, Asem M. ; Farag, Aly A. ; Gimel´farb, Georgy
Author_Institution :
Comput. Vision & Image Process. Lab., Univ. of Louisville, Louisville, KY
fYear :
2008
fDate :
8-11 Dec. 2008
Firstpage :
1
Lastpage :
4
Abstract :
This paper proposes a new analytical method for estimating parameters of a homogeneous isotropic Potts model with an asymmetric Gibbs potential function. The model is generalized by including both pairwise and triple cliques. The maximum likelihood estimates of the cliques potentials are obtained by a further elaboration of the approximate analytical estimator proposed in. Experiments with synthetic textures have shown that our potential estimates are more accurate and practicable than their counterparts obtained with classical methods.
Keywords :
Markov processes; Potts model; image texture; maximum likelihood estimation; MGRF Potts model; Markov-Gibbs random field models; asymmetric Gibbs potential function; homogeneous isotropic Potts model; maximum likelihood estimation; parameter estimation; synthetic textures; Computer vision; Equations; Image analysis; Image processing; Laboratories; Least squares methods; Maximum likelihood estimation; Parameter estimation; Pixel; Probability distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location :
Tampa, FL
ISSN :
1051-4651
Print_ISBN :
978-1-4244-2174-9
Electronic_ISBN :
1051-4651
Type :
conf
DOI :
10.1109/ICPR.2008.4761339
Filename :
4761339
Link To Document :
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