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Hyperspectral unmixing with simultaneous dimensionality estimation

dc.contributor.authorNascimento, Jose
dc.contributor.authorBioucas-Dias, José M.
dc.date.accessioned2016-05-27T13:14:24Z
dc.date.available2016-05-27T13:14:24Z
dc.date.issued2012
dc.description.abstractThis paper is an elaboration of the simplex identification via split augmented Lagrangian (SISAL) algorithm (Bioucas-Dias, 2009) to blindly unmix hyperspectral data. SISAL is a linear hyperspectral unmixing method of the minimum volume class. This method solve a non-convex problem by a sequence of augmented Lagrangian optimizations, where the positivity constraints, forcing the spectral vectors to belong to the convex hull of the endmember signatures, are replaced by soft constraints. With respect to SISAL, we introduce a dimensionality estimation method based on the minimum description length (MDL) principle. The effectiveness of the proposed algorithm is illustrated with simulated and real data.pt_PT
dc.identifier.citationNASCIMENTO, José M. P.; BIOUCAS-DIAS, José M. - Hyperspectral unmixing with simultaneous dimensionality estimation. ICPRAM 2012 - International Conference on Pattern Recognition Applications and Methods. 2012pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.21/6216
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectBlind hyperspectral unmixingpt_PT
dc.subjectMinimum volume simplexpt_PT
dc.subjectMinimum Description Lengthpt_PT
dc.subjectMDLpt_PT
dc.subjectVariable splitting augmented Lagrangianpt_PT
dc.subjectDimensionality reductionpt_PT
dc.titleHyperspectral unmixing with simultaneous dimensionality estimationpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceVilamoura, Portugalpt_PT
oaire.citation.endPage444pt_PT
oaire.citation.startPage438pt_PT
oaire.citation.titleICPRAM 2012 - International Conference on Pattern Recognition Applications and Methodspt_PT
person.familyNameNascimento
person.givenNameJose
person.identifier.ciencia-id6912-6F61-1964
person.identifier.orcid0000-0002-5291-6147
person.identifier.ridE-6212-2015
person.identifier.scopus-author-id55920018000
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationc7ffc6c0-1bdc-4f47-962a-a90dfb03073c
relation.isAuthorOfPublication.latestForDiscoveryc7ffc6c0-1bdc-4f47-962a-a90dfb03073c

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