0360244 20240903170623.220110707235959.9 000293207900011 83455221186 Probabilistic mixture-based image modelling 19 s. cav_un_epca*02971630023-5954Kybernetika473 (2011)482-500Ústav teorie informace a automatizace AV ČR, v. v. i. BTF texture modelling discrete distribution mixtures Bernoulli mixture Gaussian mixture multi-spectral texture modelling 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*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. cav_un_auth*0101091 Grim Jiří 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/2011/RO/haindl-0360244.pdf 1M0572 GA MŠk cav_un_auth*0001814 387/2010 CESNET CZ 2C06019 GA MŠk CZ cav_un_auth*0216518 GA102/08/0593 GA ČR cav_un_auth*0239567 GA103/11/0335 GA ČR CZ CEZ:AV0Z10750506 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. 2012 BD 4 A O 4a 4o 20231122134558.2 http://hdl.handle.net/11104/0197840 COMPUTERSCIENCECYBERNETICS 0.473 0.033 9.5 0.0016 0.277 403 61 21 0.307 20.45 0.61 Q2 23.915 17.500 Q4 Q3 2011 Soubory v repozitáři: Haindl-0360244.pdf, 0360244.pdf 83455221186 SCOPUS 000293207900011 WOS cav_un_epca*0297163 Kybernetika 0023-5954 Roč. 47 č. 3 2011 482 500 Ústav teorie informace a automatizace AV ČR, v. v. i.