Počet záznamů: 1
Probabilistic mixture-based image modelling
- 1.0360244 - ÚTIA 2012 RIV CZ eng J - Článek v odborném periodiku
Haindl, Michal - Havlíček, Vojtěch - Grim, Jiří
Probabilistic mixture-based image modelling.
Kybernetika. Roč. 47, č. 3 (2011), s. 482-500. ISSN 0023-5954
Grant CEP: GA MŠk 1M0572; GA ČR GA102/08/0593
Grant ostatní:CESNET(CZ) 387/2010; GA MŠk(CZ) 2C06019; GA ČR(CZ) GA103/11/0335
Výzkumný záměr: CEZ:AV0Z10750506
Klíčová slova: BTF texture modelling * discrete distribution mixtures * Bernoulli mixture * Gaussian mixture * multi-spectral texture modelling
Kód oboru RIV: BD - Teorie informace
Impakt faktor: 0.454, rok: 2011
During the last decade we have introduced probabilistic mixture models into image modelling area, which present highly atypical and extremely demanding applications for these models. This difficulty arises from the necessity to model tens thousands correlated data simultaneously and to reliably learn such unusually complex mixture models. Presented paper surveys these novel generative colour image models based on multivariate discrete, Gaussian or Bernoulli mixtures, respectively and demonstrates their major advantages and drawbacks on texture modelling applications. Our mixture models are restricted to represent two-dimensional visual information. Thus a measured 3D multispectral texture is spectrally factorized and corresponding multivariate mixture models are further learned from single orthogonal mono-spectral components and used to synthesise and enlarge these mono-spectral factor components.
Trvalý link: http://hdl.handle.net/11104/0197840
Počet záznamů: 1