Multiscale Texture Segmentation of Dip-cube Slices using Wavelet-domain Hidden Markov Trees

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dc.citation.bibtexNameinproceedingsen_US
dc.citation.conferenceNameProceedings of the SEG Meetingen_US
dc.citation.locationHouston, TXen_US
dc.contributor.authorMagrin-Chagnolleau, Ivanen_US
dc.contributor.authorChoi, Hyeokhoen_US
dc.contributor.authorvan Spaendonck, Rutgeren_US
dc.contributor.authorSteeghs, Philippeen_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:52:35Zen_US
dc.date.available2007-10-31T00:52:35Zen_US
dc.date.issued1999-11-01en_US
dc.date.modified2006-06-05en_US
dc.date.note2004-11-10en_US
dc.date.submitted1999-11-01en_US
dc.descriptionConference Paperen_US
dc.description.abstractWavelet-domain Hidden Markov Models (HMMs) are powerful tools for modeling the statistical properties of wavelet coefficients. By characterizing the joint statistics of wavelet coefficients, HMMs efficiently capture the characteristics of many real-world signals. When applied to images, the model can characterize the joint statistics between pixels, providing a very good classifier for textures. Utilizing the inherent tree structure of wavelet-domain HMM, classification of textures at various scales is possible, furnishing a natural tool for multiscale texture segmentation. In this paper, we introduce a new multiscale texture segmentation algorithm based on wavelet-domain HMM. Based on the multiscale classification results obtained from the wavelet-domain HMM, we develop a method to combine the multiscale classification results to generate a reliable segmentation of the texture images. We apply this new technique to the segmentation of dip-cube slices.en_US
dc.identifier.citationI. Magrin-Chagnolleau, H. Choi, R. van Spaendonck, P. Steeghs and R. G. Baraniuk, "Multiscale Texture Segmentation of Dip-cube Slices using Wavelet-domain Hidden Markov Trees," 1999.en_US
dc.identifier.urihttps://hdl.handle.net/1911/20079en_US
dc.language.isoengen_US
dc.subjectsegmentationen_US
dc.subjecthidden markov treesen_US
dc.subject.keywordsegmentationen_US
dc.subject.keywordhidden markov treesen_US
dc.subject.otherSignal Processing Applicationsen_US
dc.titleMultiscale Texture Segmentation of Dip-cube Slices using Wavelet-domain Hidden Markov Treesen_US
dc.typeConference paperen_US
dc.type.dcmiTexten_US
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