Publication
Hyperspectral image reconstruction of heritage artwork using RGB images and deep neural networks
| dc.contributor.author | Chen, Ailin | |
| dc.contributor.author | Jesus, Rui | |
| dc.contributor.author | Vilarigues, M. | |
| dc.date.accessioned | 2023-05-08T07:38:38Z | |
| dc.date.available | 2023-05-08T07:38:38Z | |
| dc.date.issued | 2022-10 | |
| dc.description.abstract | The application of our research is in the art world where the scarcity of available analytical data from a particular artist or physical access for its acquisition is restricted. This poses a fundamental problem for the purpose of conservation, restoration or authentication of historical artworks. We address part of this problem by providing a practical method to generate hyperspectral data from readily available RGB imagery of artwork by means of a two-step process using deep neural networks. The particularities of our approach include the generation of learnable colour mixtures and reflectances from a reduced collection of prior data for the mapping and reconstruction of hyperspectral features on new images. Further analysis and correction of the prediction are achieved by a second network that reduces the error by producing results akin to those obtained by a hyperspectral camera. Our method has been used to study a collection of paintings by Amadeo de Souza-Cardoso where successful results were obtained. CCS CONCEPTS • Computing methodologies → Neural networks; Artificial intelligence; • Applied computing → Arts and humanities. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | CHEN, Ailin; JESUS, Rui; VILARIGUES, Márcia – Hyperspectral image reconstruction of heritage artwork using RGB images and deep neural networks. In CBMI '22: Proceedings of the 19th International Conference on Content-based Multimedia Indexing. Graz, Austria: Association for Computing Machinary, 2022. ISBN 978-1-4503-9720-9. Pp. 97-102. | pt_PT |
| dc.identifier.doi | 10.1145/3549555.3549583 | pt_PT |
| dc.identifier.isbn | 978-1-4503-9720-9 | |
| dc.identifier.uri | http://hdl.handle.net/10400.21/15984 | |
| dc.language.iso | eng | pt_PT |
| dc.publisher | Association for Computing Machinary | pt_PT |
| dc.relation | NOVA Laboratory for Computer Science and Informatics | |
| dc.relation | Glass and Ceramic for the Arts | |
| dc.relation | Image and materials of Amadeo de Souza-Cardoso for an AI authentication tool | |
| dc.relation.publisherversion | https://dl.acm.org/doi/pdf/10.1145/3549555.3549583 | pt_PT |
| dc.subject | Neural networks | pt_PT |
| dc.subject | Hyperspectral imaging | pt_PT |
| dc.subject | Image visualisation | pt_PT |
| dc.subject | Colour analysis | pt_PT |
| dc.title | Hyperspectral image reconstruction of heritage artwork using RGB images and deep neural networks | pt_PT |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.awardTitle | NOVA Laboratory for Computer Science and Informatics | |
| oaire.awardTitle | Glass and Ceramic for the Arts | |
| oaire.awardTitle | Image and materials of Amadeo de Souza-Cardoso for an AI authentication tool | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04516%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00729%2F2020/PT | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT//PD%2FBD%2F135223%2F2017/PT | |
| oaire.citation.conferencePlace | September 14–16, 2022 - Graz, Austria | pt_PT |
| oaire.citation.endPage | 102 | pt_PT |
| oaire.citation.startPage | 97 | pt_PT |
| oaire.citation.title | CBMI '22: Proceedings of the 19th International Conference on Content-based Multimedia Indexing | pt_PT |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| person.familyName | Jesus | |
| person.familyName | Vilarigues | |
| person.givenName | Rui | |
| person.givenName | Márcia | |
| person.identifier | 2682439 | |
| person.identifier.ciencia-id | 041D-93A6-7412 | |
| person.identifier.ciencia-id | B417-B4B6-E982 | |
| person.identifier.orcid | 0000-0003-1869-6491 | |
| person.identifier.orcid | 0000-0003-4134-2819 | |
| person.identifier.scopus-author-id | 23012170100 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | conferenceObject | pt_PT |
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