The Effect of Dictionary Learning Algorithms on Super-resolution Hyperspectral Reconstruction

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dc.contributor.authorSimsek, Murat
dc.contributor.authorPolat, Ediz
dc.date.accessioned2020-06-25T18:15:55Z
dc.date.available2020-06-25T18:15:55Z
dc.date.issued2015
dc.departmentKırıkkale Üniversitesi
dc.descriptionInternational Conference Information Communication Automation Technologies (ICAT) -- OCT 29-31, 2015 -- Sarajevo, BOSNIA & HERCEG
dc.description.abstractThe spatial resolutions of hyperspectral images are generally lower due to imaging hardware limitations. Super-resolution algorithms can be applied to obtain higher resolutions. Many algorithms exist to achieve super-resolution hyperspectral images from low resolution images acquired in different wavelengths. One of the popular algorithms is sparse representation-based algorithms that employ dictionary learning methods. In this study, a comparative framework is developed to investigate which dictionary learning algorithm leads to better super-resolution images. In order to achieve that, K-SVD and ODL dictionary learning algorithms are employed for comparison. A sparse representation-based algorithm G-SOMP+ is used for hyperspectral super-resolution reconstruction. The experimental results show that ODL algorithm outperforms K-SVD in terms of both reconstruction quality and processing times.en_US
dc.description.sponsorshipUniv Sarajevo, Fac Elect Engn Sarajevo, IEEE, IEEE CSS, IEEE Comp Soc, IEEE SMCen_US
dc.identifier.citationclosedAccessen_US
dc.identifier.isbn978-1-4673-8146-8
dc.identifier.scopus2-s2.0-84960935756
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12587/6344
dc.identifier.wosWOS:000380438700014
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIeeeen_US
dc.relation.ispartof2015 Xxv International Conference On Information, Communication And Automation Technologies (Icat)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectHyperspectralen_US
dc.subjectsuper-resolutionen_US
dc.subjectsparse respresentationen_US
dc.subjectdictionary learningen_US
dc.titleThe Effect of Dictionary Learning Algorithms on Super-resolution Hyperspectral Reconstructionen_US
dc.typeConference Object

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