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Vertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral data

dc.contributor.authorNascimento, Jose
dc.contributor.authorBioucas-Dias, José M.
dc.date.accessioned2014-06-05T11:35:26Z
dc.date.available2014-06-05T11:35:26Z
dc.date.issued2003-06
dc.descriptionChapter in Book Proceedings with Peer Review First Iberian Conference, IbPRIA 2003, Puerto de Andratx, Mallorca, Spain, JUne 4-6, 2003. Proceedingspor
dc.description.abstractLinear spectral mixture analysis, or linear unmixing, has proven to be a useful tool in hyperspectral remote sensing applications. It aims at estimating the number of reference substances, also called endmembers, their spectral signature and abundance fractions, using only the observed data (mixed pixels). This paper presents new method that performs unsupervised endmember extraction from hyperspectral data. The algorithm exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm complexity, measured in floating points operations, is O(n), where n is the sample size. The effectiveness of the proposed scheme is illustrated using simulated data.por
dc.identifier.citationNASCIMENTO, José M. P.; BIOUCAS-DIAS, José M. - Vertex Component Analysis: A Fast Algorithm to Extract Endmembers Spectra from Hyperspectral Data. Pattern Recognition and Image Analysis. ISBN 978-3-540-40217-6. Vol. 2652 (2003), p. 626-635.por
dc.identifier.isbn978-3-540-40217-6
dc.identifier.isbn978-3-540-44871-6
dc.identifier.other10.1007/978-3-540-44871-6_73
dc.identifier.urihttp://hdl.handle.net/10400.21/3614
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherSpringer Berlin Heidelbergpor
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.relation.publisherversionhttp://link.springer.com/chapter/10.1007%2F978-3-540-44871-6_73por
dc.subjectLinear spectral mixture analysispor
dc.subjectLinear unmixingpor
dc.subjectHyperspectral remote sensing applicationspor
dc.titleVertex component analysis: a fast algorithm to extract endmembers spectra from hyperspectral datapor
dc.typebook part
dspace.entity.typePublication
oaire.citation.conferencePlacePuerto de Andratxpor
oaire.citation.endPage635por
oaire.citation.startPage626por
oaire.citation.titlePattern Recognition and Image Analysispor
oaire.citation.volume2652por
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.rightsrestrictedAccesspor
rcaap.typebookPartpor
relation.isAuthorOfPublicationc7ffc6c0-1bdc-4f47-962a-a90dfb03073c
relation.isAuthorOfPublication.latestForDiscoveryc7ffc6c0-1bdc-4f47-962a-a90dfb03073c

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