Texture Synthesis Using Single-Scale / Multiple-Scale Markov Random Field Models

Abstract: 
This fast multigrid colour texture synthesis algorithm starts with spectral factorization of an input colour texture image using the Karhunen-Loeve expansion. Single orthogonal monospectral components are further decomposed into a multi-resolution grid and each resolution factors are independently modeled by their dedicated Markov random field model. Finally single synthesized monospectral single-resolution texture factorss are collapsed into the fine resolution images and using the inverse Karhunen-Loeve transformation we obtain the required colour texture.

 

The multiresolution algorithm.

Examples