Hyperspectral imaging using notions from type-2 fuzzy sets

dc.contributor.authorLópez Maestresalas, Ainara
dc.contributor.authorMiguel Turullols, Laura de
dc.contributor.authorLópez Molina, Carlos
dc.contributor.authorArazuri Garín, Silvia
dc.contributor.authorBustince Sola, Humberto
dc.contributor.authorJarén Ceballos, Carmen
dc.contributor.departmentIngenieríaes_ES
dc.contributor.departmentIngeniaritzaeu
dc.contributor.departmentEstadística, Informática y Matemáticases_ES
dc.contributor.departmentEstatistika, Informatika eta Matematikaeu
dc.contributor.funderUniversidad Pública de Navarra / Nafarroako Unibertsitate Publikoaes
dc.date.accessioned2020-01-07T12:20:40Z
dc.date.available2020-01-07T12:20:40Z
dc.date.issued2019
dc.description.abstractFuzzy set theory has developed a prolific armamentarium of mathematical tools for each of the topics that has fallen within its scope. One of such topics is data comparison, for which a range of operators has been presented in the past. These operators can be used within the fuzzy set theory, but can also be ported to other scenarios in which data are provided in various representations. In this work, we elaborate on notions for type-2 fuzzy sets, specifically for the comparison of type-2 fuzzy membership degrees, to create function comparison operators. We further apply these operators to hyperspectral imaging, in which pixelwise data are provided as functions over a certain energy spectra. The performance of the functional comparison operators is put to the test in the context of in-laboratory hyperspectral image segmentation.en
dc.description.sponsorshipThis work has been partially funded by the Ministry of Science of the Spanish Government (TIN2016-77356-P) and the Research Services of the Universidad Publica de Navarra.en
dc.format.extent22 p.
dc.format.mimetypeapplication/pdfen
dc.identifier.doi10.1007/s00500-018-3208-8
dc.identifier.issn1432-7643
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/35995
dc.language.isoengen
dc.publisherSpringeren
dc.relation.ispartofSoft Computing, 23 (6), 1779-1793en
dc.relation.projectIDinfo:eu-repo/grantAgreement/ES/1PE/TIN2016-77356-P/
dc.relation.publisherversionhttps://doi.org/10.1007/s00500-018-3208-8
dc.rights© Springer-Verlag GmbH Germany, part of Springer Nature 2018en
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.subjectHyperspectral imagingen
dc.subjectFunction-valued arithmeticsen
dc.subjectTheory of comparisonen
dc.subjectType-2 fuzzy seten
dc.titleHyperspectral imaging using notions from type-2 fuzzy setsen
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePublication
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