Analysis of Multiscale Texture Segmentation using Wavelet-Domain Hidden Markov Trees

dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameAsilomar Conference on Signals, Systems, and Computersen_US
dc.citation.firstpage1287
dc.citation.lastpage1291
dc.citation.locationPacific Grove, CAen_US
dc.citation.volumeNumber2en_US
dc.contributor.authorChoi, Hyeokhoen_US
dc.contributor.authorHendricks, Brenten_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:46:50Z
dc.date.available2007-10-31T00:46:50Z
dc.date.issued1999-10-01en
dc.date.modified2006-06-21en_US
dc.date.note2001-10-10en_US
dc.date.submitted1999-10-01en_US
dc.descriptionConference paperen_US
dc.description.abstractThis paper describes a technique for estimating the Kullback-Leibler (KL) distance between two Hidden Markov Models (HMMs), and for measuring the quality of the estimator. It also provides some results based on applying the technique to wavelet domain Hidden Markov Tree (HMT) models used in image segmentation. The technique is easily applied, because in most situations the necessary tools (data generation and likelihood calculation) are already in place.en_US
dc.identifier.citationH. Choi, B. Hendricks and R. G. Baraniuk, "Analysis of Multiscale Texture Segmentation using Wavelet-Domain Hidden Markov Trees," vol. 2, 1999.
dc.identifier.doihttp://dx.doi.org/10.1109/ACSSC.1999.831914en_US
dc.identifier.urihttps://hdl.handle.net/1911/19950
dc.language.isoeng
dc.subjecttexture segmentation*
dc.subjectwavelet*
dc.subjecthidden marlov trees*
dc.subject.keywordtexture segmentationen_US
dc.subject.keywordwaveleten_US
dc.subject.keywordhidden marlov treesen_US
dc.subject.otherImage Processing and Pattern analysisen_US
dc.subject.otherWavelet based Signal/Image Processingen_US
dc.titleAnalysis of Multiscale Texture Segmentation using Wavelet-Domain Hidden Markov Treesen_US
dc.typeConference paper
dc.type.dcmiText
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