Identity statement area
Reference TypeConference Paper (Conference Proceedings)
Last Update2007: administrator
Metadata Last Update2020: administrator
Citation KeyLevadaMasc:2007:EsNoPo
TitleEstimation of non-homogeneous Potts-Strauss MRF model parameters on higher-order neighborhood systems by maximum pseudo-likelihood
DateOct. 7-10, 2007
Access Date2021, Jan. 19
Number of Files1
Size161 KiB
Context area
Author1 Levada, Alexandre Luis Magalhães
2 Mascarenhas, Nelson Delfino d'Ávila
Affiliation1 Universidade de São Paulo
2 Universidade Federal de São Carlos
EditorGonçalves, Luiz
Wu, Shin Ting
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 20 (SIBGRAPI)
Conference LocationBelo Horizonte
Book TitleProceedings
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
Tertiary TypeTechnical Poster
History2008-07-17 14:09:45 :: -> administrator ::
2009-08-13 20:38:42 :: administrator -> banon ::
2010-08-28 20:02:32 :: banon -> administrator ::
2020-02-19 03:06:19 :: administrator -> :: 2007
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Is the master or a copy?is the master
Content Stagecompleted
Content TypeExternal Contribution
KeywordsMarkov Random Fields, Potts-Strauss model, maximum pseudo-likelihood.
AbstractThis paper addresses the problem of maximum pseudo-likelihood estimation of the non-homogeneous Potts-Strauss image model parameters using higher-order non-causal neighborhood systems in a computationally efficient way. The motivation is the development of a new methodology for contextual classification that uses combination of sub-optimal MRF algorithms for multispectral image classification, which requires accurate parameters estimation. The results show that the method is consistent with real image data and in the presence of random noise.
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Target FileLevada_Mascarenhas_SIBGRAPI2007.pdf
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