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Parallel sparse unmixing of hyperspectral data

2014-01-27Conference object Restricted access
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dc.contributor.authorAlves, José M. Rodriguez
dc.contributor.authorNascimento, Jose
dc.contributor.authorBioucas-Dias, José M.
dc.contributor.authorPlaza, António
dc.contributor.authorSilva, Vítor
dc.date.accessioned2017-11-29T09:34:57Z
dc.date.available2017-11-29T09:34:57Z
dc.date.issued2014-01-27
dc.description.abstractIn this paper, a new parallel method for sparse spectral unmixing of remotely sensed hyperspectral data on commodity graphics processing units (GPUs) is presented. A semi-supervised approach is adopted, which relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. This method is based on the spectral unmixing by splitting and augmented Lagrangian (SUNSAL) that estimates the material's abundance fractions. The parallel method is performed in a pixel-by-pixel fashion and its implementation properly exploits the GPU architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for simulated and real hyperspectral datasets reveal significant speedup factors, up to 164 times, with regards to optimized serial implementation.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationALVES, José M. Rodriguez; [et al] – Parallel sparse unmixing of hyperspectral data. In 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS. Melbourne, VIC, Australia: IEEE, 2014. ISBN 978-1-4799-1114-1. Pp. 1446-1449.pt_PT
dc.identifier.doi10.1109/IGARSS.2013.6723057pt_PT
dc.identifier.isbn978-1-4799-1114-1
dc.identifier.issn2153-6996
dc.identifier.issn2153-7003
dc.identifier.urihttp://hdl.handle.net/10400.21/7609
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherInstitute of Electrical and Electronics Engineerspt_PT
dc.relation.publisherversionhttp://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6723057pt_PT
dc.subjectHyperspectral unmixingpt_PT
dc.subjectSparse regressionpt_PT
dc.subjectGraphics processing unitpt_PT
dc.subjectParallel methodspt_PT
dc.titleParallel sparse unmixing of hyperspectral datapt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.conferencePlaceMelbourne, Australiapt_PT
oaire.citation.endPage1449pt_PT
oaire.citation.startPage1446pt_PT
oaire.citation.title2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS (21-26 July 2013)pt_PT
person.familyNameNascimento
person.familyNameDias da Silva
person.givenNameJose
person.givenNameVítor
person.identifier.ciencia-id6912-6F61-1964
person.identifier.ciencia-idA912-8252-99D4
person.identifier.orcid0000-0002-5291-6147
person.identifier.orcid0000-0002-1862-1230
person.identifier.ridE-6212-2015
person.identifier.scopus-author-id55920018000
rcaap.rightsclosedAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublicationc7ffc6c0-1bdc-4f47-962a-a90dfb03073c
relation.isAuthorOfPublicationd0763cf1-6a95-4270-9428-53ea86b8cf35
relation.isAuthorOfPublication.latestForDiscoveryd0763cf1-6a95-4270-9428-53ea86b8cf35

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