| dc.contributor.author | Simsek, Murat | |
| dc.contributor.author | Polat, Ediz | |
| dc.date.accessioned | 2020-06-25T18:17:00Z | |
| dc.date.available | 2020-06-25T18:17:00Z | |
| dc.date.issued | 2016 | |
| dc.identifier.citation | closedAccess | en_US |
| dc.identifier.isbn | 978-1-5090-1679-2 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12587/6669 | |
| dc.description | 24th Signal Processing and Communication Application Conference (SIU) -- MAY 16-19, 2016 -- Zonguldak, TURKEY | en_US |
| dc.description | WOS: 000391250900166 | en_US |
| dc.description.abstract | Due to hardware limitations, hyperspectral imagery has low spatial resolution. It can be obtained super-resolution hyperspectral imagery by means of sparse representation-based methods that are designed for improving spatial resolution. In this paper, the effect of sparse representation-based dictionary learning algorithms including K-SVD, ODL and Bayes on obtaining superresolution images with low error and high quality has been investigated. The method with best results has been identified. | en_US |
| dc.description.sponsorship | IEEE, Bulent Ecevit Univ, Dept Elect & Elect Engn, Bulent Ecevit Univ, Dept Biomed Engn, Bulent Ecevit Univ, Dept Comp Engn | en_US |
| dc.language.iso | tur | en_US |
| dc.publisher | Ieee | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | hyperspectral images | en_US |
| dc.subject | super resolution | en_US |
| dc.subject | sparse representation | en_US |
| dc.subject | dictionary learning | en_US |
| dc.title | Sparse Representation-based Dictionary Learning Methods for Hyperspectral Super-Resolution | en_US |
| dc.type | conferenceObject | en_US |
| dc.contributor.department | Kırıkkale Üniversitesi | en_US |
| dc.identifier.startpage | 753 | en_US |
| dc.identifier.endpage | 756 | en_US |
| dc.relation.journal | 2016 24Th Signal Processing And Communication Application Conference (Siu) | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
