0443580 20240103210021.020150526235959.9 000354102200005 84928473655 10.1117/12.2077481 11 s. P cav_un_epca*0444227978-1-62841-488-20277-786XBellinghamSPIE-IS&T2015 Texture texture synthesis compound Markov random field model CAR model Potts MRF Voronoi mosaic cav_un_auth*0101093 Haindl Michal Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0286710 Remeš Václav Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101100 Havlíček Vojtěch Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/21015/RO/haindl-0443580.pdf GA14-10911S GA ČR CZ cav_un_auth*0303439 GA14-02652S GA ČR CZ cav_un_auth*0303412 This paper introduces a method for modeling mosaic-like textures using a multispectral parametric Bidirectional Texture Function (BTF) compound Markov random field model (CMRF). The primary purpose of our synthetic texture pproach is to reproduce, compress, and enlarge a given measured texture image so that ideally both natural and synthetic texture will be visually indiscernible, but the model can be easily applied for BFT material editing. The CMRF model consist of several sub-models each having different characteristics along with an underlying structure model which controls transitions between these sub models. The proposed model uses the Potts random field for distributing local texture models in the form of analytically solvable wide-sense BTF Markovian representation for single regions among the fields of a mosaic approximated by the Voronoi diagram. The control field of the BTF-CMRF is generated by the Potts random field model build on top of the adjacency graph of a measured mosaic. 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 BTF MRFs. cav_un_auth*0316990 Electronic Imaging 2015 San Francisco 08.02.2015-12.02.2015 US 2016 BD 3 PR http://hdl.handle.net/11104/0246781 1 S 0.223 Q4 2015 84928473655 SCOPUS 000354102200005 WOS cav_un_epca*0444227 Measuring, Modeling, and Reproducing Material Appearance 2015 978-1-62841-488-2 0277-786X 939807-1-939807-11 Bellingham SPIE-IS&T 2015 Proceedings of SPIE 9398