Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/10413
Full metadata record
DC FieldValueLanguage
dc.contributor.authorÖzışık Başkurt, Didem-
dc.contributor.authorBaştanlar, Yalın-
dc.contributor.authorYardımcı Çetin, Yasemin-
dc.date.accessioned2021-01-24T18:43:07Z-
dc.date.available2021-01-24T18:43:07Z-
dc.date.issued2020-
dc.identifier.issn1751-9632-
dc.identifier.issn1751-9640-
dc.identifier.urihttps://doi.org/10.1049/iet-cvi.2019.0784-
dc.identifier.urihttps://hdl.handle.net/10413-
dc.description.abstractHyperspectral imaging systems provide dense spectral information on the scene under investigation by collecting data from a high number of contiguous bands of the electromagnetic spectrum. The low spatial resolutions of these sensors frequently give rise to the mixing problem in remote sensing applications. Several unmixing approaches are developed in order to handle the challenging mixing problem on perspective images. On the other hand, omnidirectional imaging systems provide a 360-degree field of view in a single image at the expense of lower spatial resolution. In this study, we propose a novel imaging system which integrates hyperspectral cameras with mirrors so on to yield catadioptric omnidirectional imaging systems to benefit from the advantages of both modes. Catadioptric images, incorporating a camera with a reflecting device, introduce radial warping depending on the structure of the mirror used in the system. This warping causes a non-uniformity in the spatial resolution which further complicates the unmixing problem. In this context, a novel spatial-contextual unmixing algorithm specifically for the large field of view of the hyperspectral imaging system is developed. The proposed algorithm is evaluated on various real-world and simulated cases. The experimental results show that the proposed approach outperforms compared methods.en_US
dc.language.isoenen_US
dc.publisherInstitution of Engineering and Technologyen_US
dc.relation.ispartofIET Computer Visionen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.titleCatadioptric hyperspectral imaging, an unmixing approachen_US
dc.typeArticleen_US
dc.departmentIzmir Institute of Technology. Computer Engineeringen_US
dc.identifier.volume14en_US
dc.identifier.issue7en_US
dc.identifier.startpage493en_US
dc.identifier.endpage504en_US
dc.identifier.wosWOS:000598689800010-
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.cont.department-temp[Baskurt, Didem Ozisik; Cetin, Yasemin Yardimci] METU Informat Inst, Dumlupinar Bulvari 1, TR-06800 Ankara, Turkey; [Bastanlar, Yalin] IZTECH, Comp Engn Dept, TR-35430 Izmir, Turkeyen_US
dc.identifier.doi10.1049/iet-cvi.2019.0784-
dc.relation.doi10.1049/iet-cvi.2019.0784en_US
dc.coverage.doi10.1049/iet-cvi.2019.0784en_US
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.grantfulltextnone-
crisitem.author.deptDepartment of Computer Engineering-
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record

CORE Recommender

WEB OF SCIENCETM
Citations

1
checked on Oct 23, 2021

Page view(s)

40
checked on Oct 23, 2021

Google ScholarTM

Check

Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.