• 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