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