Title :
Potts compound Markovian texture model
Author :
Haindl, Michal ; Remes, Vaclav ; Havlicek, V.
Author_Institution :
Inst. of Inf. Theor. & Autom., Prague, Czech Republic
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;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4