Lossy Compressive Sensing Based on Online Dictionary Learning
| dc.contributor.author | Ulku, Irem | |
| dc.contributor.author | Kizgut, Ersin | |
| dc.date.accessioned | 2020-03-09T13:12:05Z | |
| dc.date.accessioned | 2025-09-18T16:07:36Z | |
| dc.date.available | 2020-03-09T13:12:05Z | |
| dc.date.available | 2025-09-18T16:07:36Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | In this paper, a lossy compression of hyperspectral images is realized by using a novel online dictionary learning method in which three dimensional datasets can be compressed. This online dictionary learning method and blind compressive sensing (BCS) algorithm are combined in a hybrid lossy compression framework for the first time in the literature. According to the experimental results, BCS algorithm has the best compression performance when the compression bit rate is higher than or equal to 0.5 bps. Apart from observing rate-distortion performance, anomaly detection performance is also tested on the reconstructed images to measure the information preservation performance. | en_US |
| dc.description.sponsorship | Turkish Scientific and Technical Research Council | en_US |
| dc.description.sponsorship | The authors would like to thank the anonymous reviewers for their helpful and constructive comments that greatly contributed to improving the final version of the paper. The authors would also like to thank Prof. Dr. Halil T. Eyyuboglu for useful suggestions and comments. This research was partially supported by the Turkish Scientific and Technical Research Council. | en_US |
| dc.identifier.citation | Ulku, Irem; Kizgut, Ersin, "Lossy Compressive Sensing Based on Online Dictionary Learning", Computing and Informatics, Vol. 38, No. 1, pp. 151-172, (2019). | en_US |
| dc.identifier.doi | 10.31577/cai_2019_1_151 | |
| dc.identifier.issn | 1335-9150 | |
| dc.identifier.issn | 2585-8807 | |
| dc.identifier.scopus | 2-s2.0-85072624741 | |
| dc.identifier.uri | https://doi.org/10.31577/cai_2019_1_151 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12416/14814 | |
| dc.language.iso | en | en_US |
| dc.publisher | Slovak Acad Sciences inst informatics | en_US |
| dc.relation.ispartof | Computing and Informatics | |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Hyperspectral Imaging | en_US |
| dc.subject | Compression Algorithms | en_US |
| dc.subject | Dictionary Learning | en_US |
| dc.subject | Sparse Coding | en_US |
| dc.title | Lossy Compressive Sensing Based on Online Dictionary Learning | en_US |
| dc.title | Lossy Compressive Sensing Based on Online Dictionary Learning | tr_TR |
| dc.type | Article | en_US |
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| gdc.author.wosid | Ulku,, Irem/Ahd-8857-2022 | |
| gdc.author.wosid | Kızgut, Ersin/M-3074-2018 | |
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| gdc.description.department | Çankaya University | en_US |
| gdc.description.departmenttemp | [Ulku, Irem] Cankaya Univ, Dept Elect & Elect Engn, Eskisehir Yolu 29 Km, TR-06790 Ankara, Turkey; [Kizgut, Ersin] Univ Politecn Valencia, IUMPA, E-46071 Valencia, Spain | en_US |
| gdc.description.endpage | 172 | en_US |
| gdc.description.issue | 1 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
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| gdc.description.startpage | 151 | en_US |
| gdc.description.volume | 38 | en_US |
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| gdc.oaire.keywords | Hyperspectral imaging | |
| gdc.oaire.keywords | sparse coding | |
| gdc.oaire.keywords | 68U10 | |
| gdc.oaire.keywords | compression algorithms | |
| gdc.oaire.keywords | dictionary learning | |
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