• DocumentCode
    594648
  • Title

    Potts compound Markovian texture model

  • Author

    Haindl, Michal ; Remes, Vaclav ; Havlicek, V.

  • Author_Institution
    Inst. of Inf. Theor. & Autom., Prague, Czech Republic
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    29
  • Lastpage
    32
  • Abstract
    This paper describes a novel multispectral parametric compound Markov random field model for texture synthesis. The proposed compound Markov random field model connects a parametric control random field represented by a hierarchical Potts Markov random field model with analytically solvable wide-sense Markovian representation for single regions. The compound random field synthesis combines the modified fast Swendsen-Wang Markov Chain Monte Carlo sampling of the hierarchical Potts MRF part with the fast and analytical synthesis of single regional MRFs.
  • Keywords
    Markov processes; Monte Carlo methods; image texture; Markovian representation; Potts compound Markovian texture model; compound Markov random field model; hierarchical Potts MRF; modified fast Swendsen-Wang Markov Chain Monte Carlo sampling; novel multispectral parametric compound Markov random field model; parametric control random field; texture synthesis; Analytical models; Compounds; Data models; Markov processes; Mathematical model; Numerical models; Solid modeling;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460064