Potts Compound Markovian Texture Model
Michal Haindl, Václav Remeš, Vojtěch Havlíček · ASEP · 2012
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.