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Parallel method for sparse semisupervised hyperspectral unmixing

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dc.contributor.authorNascimento, Jose
dc.contributor.authorRodríguez Alves, José M.
dc.contributor.authorPlaza, Antonio
dc.contributor.authorSilva, Vítor
dc.contributor.authorBioucas-Dias, José M.
dc.date.accessioned2016-05-02T11:47:22Z
dc.date.available2016-05-02T11:47:22Z
dc.date.issued2013
dc.description.abstractParallel hyperspectral unmixing problem is considered in this paper. A semisupervised approach is developed under the linear mixture model, where the abundance's physical constraints are taken into account. The proposed approach relies on the increasing availability of spectral libraries of materials measured on the ground instead of resorting to endmember extraction methods. Since Libraries are potentially very large and hyperspectral datasets are of high dimensionality a parallel implementation in a pixel-by-pixel fashion is derived to properly exploits the graphics processing units (GPU) architecture at low level, thus taking full advantage of the computational power of GPUs. Experimental results obtained for real hyperspectral datasets reveal significant speedup factors, up to 164 times, with regards to optimized serial implementation.pt_PT
dc.identifier.citationNASCIMENTO, José M. P.; [et al] - Parallel method for sparse semisupervised hyperspectral unmixing. HIGH-Performance computing in remote sensing III. ISSN 0277-786X. Vol. 8895. 2013pt_PT
dc.identifier.doi10.1117/12.2029206pt_PT
dc.identifier.isbn978-0-8194-9764-2
dc.identifier.issn0277-786X
dc.identifier.urihttp://hdl.handle.net/10400.21/6138
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherSPIEpt_PT
dc.relation.ispartofseriesProceedings of SPIE;88950B
dc.subjectHyperspectral imagingpt_PT
dc.subjectSparse unmixingpt_PT
dc.subjectSparse regressionpt_PT
dc.subjectGraphics processing unitpt_PT
dc.subjectGPUpt_PT
dc.subjectParallel methodspt_PT
dc.subjectSpectral librariespt_PT
dc.titleParallel method for sparse semisupervised hyperspectral unmixingpt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.citation.titleHIGH-Performance computing in remote sensing IIIpt_PT
oaire.citation.volume8895pt_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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