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dc.contributor.authorTong, Lei
dc.contributor.authorZhou, Jun
dc.contributor.authorQian, Yuntao
dc.contributor.authorGao, Yongsheng
dc.contributor.editorNaoto Yokoya, Jocelyn Chanussot
dc.date.accessioned2017-12-19T01:54:22Z
dc.date.available2017-12-19T01:54:22Z
dc.date.issued2015
dc.identifier.isbn9781467390156
dc.identifier.issn2158-6268
dc.identifier.doi10.1109/WHISPERS.2015.8075468
dc.identifier.urihttp://hdl.handle.net/10072/355892
dc.description.abstractHyperspectral unmixing is an important technique for estimating fraction of different land covers from remote sensing imagery. In recent years, nonnegative matrix factorization (NMF) methods with various constraints have been introduced into hyperspectral unmixing. Among these methods, graph based constraint has been proved to be useful in capturing the latent manifold structure of the hyper-spectral data in the feature domain. However, due to the complexity of the data, only using single graph can not adequately reflect the intrinsic property of the data. In this paper, we propose a multiple graph regularized NMF method for hyperspectral unmixing, which approximates the manifold and consistency of data by a linear combination of several graphs constructed in different scales. Results on both synthetic and real data have validated the effectiveness of the proposed method, and shown that it has outperformed several state-of-the-arts hyperspectral unmixing methods.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.publisher.placeUnited States
dc.relation.ispartofconferencename7th Workshop on Hyperspectral Image and Signal Processing - Evolution in Remote Sensing (WHISPERS)
dc.relation.ispartofconferencetitle2015 7TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS)
dc.relation.ispartofdatefrom2015-06-02
dc.relation.ispartofdateto2015-06-05
dc.relation.ispartoflocationTokyo, JAPAN
dc.relation.ispartofpagefrom4 pages
dc.relation.ispartofpageto4 pages
dc.relation.ispartofvolume2015-June
dc.subject.fieldofresearchImage Processing
dc.subject.fieldofresearchcode080106
dc.titleMultiple graph regularized NMF for hyperspectral unmixing
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionAccepted Manuscript (AM)
gro.facultyGriffith Sciences, Griffith School of Engineering
gro.rights.copyright© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
gro.griffith.authorGao, Yongsheng
gro.griffith.authorZhou, Jun
gro.griffith.authorTong, Lei


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