Large-Scale Hyperspectral Image Compression Via Sparse Representations Based on Online Learning
| dc.contributor.author | Ulku, Irem | |
| dc.contributor.author | Kizgut, Ersin | |
| dc.date.accessioned | 2018-09-12T13:15:57Z | |
| dc.date.accessioned | 2025-09-18T12:06:45Z | |
| dc.date.available | 2018-09-12T13:15:57Z | |
| dc.date.available | 2025-09-18T12:06:45Z | |
| dc.date.issued | 2018 | |
| dc.description | Kizgut, Ersin/0000-0002-9642-0442 | en_US |
| dc.description.abstract | In this study, proximity based optimization algorithms are used for lossy compression of hyperspectral images that are inherently large scale. This is the first time that such proximity based optimization algorithms are implemented with an online dictionary learning method. Compression performances are compared with the one obtained by various sparse representation algorithms. As a result, proximity based optimization algorithms are listed among the three best ones in terms of compression performance values for all hyperspectral images. Additionally, the applicability of anomaly detection is tested on the reconstructed images. | 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. They are also thankful to Prof. Halil T. Eyyuboglu for his useful suggestions and comments. This research was partially supported by the Turkish Scientific and Technical Research Council. | en_US |
| dc.identifier.citation | Ülkü, İ., Kizgut, E. (2018). Large-scale hyperspectral image compression via sparse representations based on online learning. International Journal Of Applied Mathematics And Computer Science, 28(1), 197-207. http://dx.doi.org/10.2478/amcs-2018-0015 | en_US |
| dc.identifier.doi | 10.2478/amcs-2018-0015 | |
| dc.identifier.issn | 1641-876X | |
| dc.identifier.issn | 2083-8492 | |
| dc.identifier.scopus | 2-s2.0-85049000853 | |
| dc.identifier.uri | https://doi.org/10.2478/amcs-2018-0015 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12416/10979 | |
| dc.language.iso | en | en_US |
| dc.publisher | Univ Zielona Gora Press | en_US |
| dc.relation.ispartof | International Journal of Applied Mathematics and Computer Science | |
| dc.rights | info:eu-repo/semantics/openAccess | 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 | Large-Scale Hyperspectral Image Compression Via Sparse Representations Based on Online Learning | en_US |
| dc.title | Large-scale hyperspectral image compression via sparse representations based on online learning | tr_TR |
| dc.type | Article | en_US |
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| gdc.author.id | Kizgut, Ersin/0000-0002-9642-0442 | |
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| gdc.author.wosid | Ulku,, Irem/Ahd-8857-2022 | |
| gdc.author.wosid | Kizgut, 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, Univ Inst Pure & Appl Math IUMPA, E-46071 Valencia, Spain | en_US |
| gdc.description.endpage | 207 | 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 | 197 | en_US |
| gdc.description.volume | 28 | en_US |
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| gdc.oaire.keywords | hyperspectral imaging | |
| gdc.oaire.keywords | sparse coding | |
| gdc.oaire.keywords | Electronic computers. Computer science | |
| gdc.oaire.keywords | QA1-939 | |
| gdc.oaire.keywords | compression algorithms | |
| gdc.oaire.keywords | QA75.5-76.95 | |
| gdc.oaire.keywords | dictionary learning | |
| gdc.oaire.keywords | Mathematics | |
| gdc.oaire.keywords | Learning and adaptive systems in artificial intelligence | |
| gdc.oaire.keywords | Computing methodologies for image processing | |
| gdc.oaire.keywords | Coding and information theory (compaction, compression, models of communication, encoding schemes, etc.) (aspects in computer science) | |
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| gdc.virtual.author | Kızgut, Ersin | |
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