dc.creatorGONZALO JORGE URCID SERRANO
dc.date2011
dc.date.accessioned2022-10-12T20:14:50Z
dc.date.available2022-10-12T20:14:50Z
dc.identifierhttp://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1436
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/4130587
dc.descriptionIn this manuscript we propose a method for the autonomous determination of endmembers in hyperspectral imagery based on recent theoretical advancements on lattice autoassociative memories. Given a hyperspectral image, the lattice algebra approach finds in a single-pass all possible candidate endmembers from which various affinely independent sets of final endmembers may be derived. In contrast to other endmember detection methods, the endmembers found using two dual canonical lattice matrices are geometrically linked to the data set spectra. The mathematical foundation of the proposed method is first described in some detail followed by application examples that illustrate the key steps of the proposed lattice based method.
dc.formatapplication/pdf
dc.languageeng
dc.publisherInformation Sciences
dc.relationcitation:Ritter, Gerhard X. and Urcid Serrano, G. (2011). A lattice matrix method for hyperspectral image unmixing, Information Sciences. Vol. 181(10):1787–1803
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0
dc.subjectinfo:eu-repo/classification/Inspec/Neural networks: Associative memories
dc.subjectinfo:eu-repo/classification/Inspec/Lattice associative memories
dc.subjectinfo:eu-repo/classification/Inspec/Lattice algebra: affine independence
dc.subjectinfo:eu-repo/classification/Inspec/Lattice independence
dc.subjectinfo:eu-repo/classification/Inspec/Lattice matrices
dc.subjectinfo:eu-repo/classification/Inspec/Hyperspectral image analysis: endmember
dc.subjectinfo:eu-repo/classification/cti/1
dc.subjectinfo:eu-repo/classification/cti/22
dc.subjectinfo:eu-repo/classification/cti/2209
dc.subjectinfo:eu-repo/classification/cti/2209
dc.titleA lattice matrix method for hyperspectral image unmixing
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.audiencestudents
dc.audienceresearchers
dc.audiencegeneralPublic


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