Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6421
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dc.contributor.authorAlbayrak, R. Tufan-
dc.contributor.authorGürbüz, Ali Cafer-
dc.contributor.authorGunyel, Bertan-
dc.date.accessioned2021-09-11T15:36:24Z-
dc.date.available2021-09-11T15:36:24Z-
dc.date.issued2014en_US
dc.identifier.citation22nd IEEE Signal Processing and Communications Applications Conference (SIU) -- APR 23-25, 2014 -- Karadeniz Teknik Univ, Trabzon, TURKEYen_US
dc.identifier.isbn978-1-4799-4874-1-
dc.identifier.issn2165-0608-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/6421-
dc.description.abstractIn hyperspectral images the measured spectra for each pixel can be modeled as convex combination of small number of endmember spectra. Since the measured structure contains only a few of possible responses out of possibly many materials sparsity based convex optimization techniques or compressive sensing can be used for hyperspectral unmixing. In this work varying sparsity based techniques are tested for hyperspectral unmixing problem. Performance analysis of these techniques on sparsity level and measurement number are performed. Effect of high coherence of hyperspectral dictionaries is disccussed and effect of signal to noise ratio is analyzed.en_US
dc.description.sponsorshipIEEE, Karadeniz Tech Univ, Dept Comp Engn & Elect & Elect Engnen_US
dc.language.isotren_US
dc.publisherIEEEen_US
dc.relation.ispartof2014 22Nd Signal Processing And Communications Applications Conference (Siu)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHyperspecytral unmixingen_US
dc.subjectcompressive sensingen_US
dc.subjectsparsityen_US
dc.subjectconvex optimizationen_US
dc.titleCompressed Sensing Based Hyperspectral Unmixingen_US
dc.typeConference Objecten_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conferenceen_US
dc.departmentFaculties, Faculty of Engineering, Department of Electrical and Electronics Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümütr_TR
dc.identifier.startpage1438en_US
dc.identifier.endpage1441en_US
dc.authorid0000-0001-8923-0299-
dc.identifier.wosWOS:000356351400339en_US
dc.identifier.scopus2-s2.0-84903761087en_US
dc.institutionauthorGürbüz, Ali Cafer-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.relation.conference22nd IEEE Signal Processing and Communications Applications Conference (SIU)en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairetypeConference Object-
item.cerifentitytypePublications-
item.languageiso639-1tr-
Appears in Collections:Elektrik ve Elektronik Mühendisliği Bölümü / Department of Electrical & Electronics Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
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