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Documenting Paintings with Gigapixel Photography

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Documenting Paintings with Gigapixel Photography

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dc.contributor.author Cabezos Bernal, Pedro Manuel es_ES
dc.contributor.author Rodríguez Navarro, Pablo es_ES
dc.contributor.author Gil Piqueras, Teresa es_ES
dc.date.accessioned 2022-11-07T19:01:57Z
dc.date.available 2022-11-07T19:01:57Z
dc.date.issued 2021-08 es_ES
dc.identifier.uri http://hdl.handle.net/10251/189397
dc.description.abstract [EN] Digital photographic capture of pictorial artworks with gigapixel resolution (around 1000 megapixels or greater) is a novel technique that is beginning to be used by some important international museums as a means of documentation, analysis, and dissemination of their masterpieces. This line of research is extremely interesting, not only for art curators and scholars but also for the general public. The results can be disseminated through online virtual museum displays, offering a detailed interactive visualization. These virtual visualizations allow the viewer to delve into the artwork in such a way that it is possible to zoom in and observe those details, which would be negligible to the naked eye in a real visit. Therefore, this kind of virtual visualization using gigapixel images has become an essential tool to enhance cultural heritage and to make it accessible to everyone. Since today's professional digital cameras provide images of around 40 megapixels, obtaining gigapixel images requires some special capture and editing techniques. This article describes a series of photographic methodologies and equipment, developed by the team of researchers, that have been put into practice to achieve a very high level of detail and chromatic fidelity, in the documentation and dissemination of pictorial artworks. The result of this research work consisted in the gigapixel documentation of several masterpieces of the Museo de Bellas Artes of Valencia, one of the main art galleries in Spain. The results will be disseminated through the Internet, as will be shown with some examples. es_ES
dc.description.sponsorship This research was carried out within the Research Project entitled Captura fotografica de resolucion gigapixel para la documentacion y divulgacion del patrimonio pictorico (01/01/19-01/01/21), reference SP20180066. Project funded with the help of Primeros Proyectos de Investigacion (PAID-06-18), Vicerrectorado de Investigacion,Innovacion y Transferencia de la Universitat Politecnica de Valencia (UPV), Valencia, Spain. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Journal of imaging es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Gigapixel photography es_ES
dc.subject Ultra-high resolution es_ES
dc.subject Art documentation es_ES
dc.subject Stitching es_ES
dc.subject Image registration es_ES
dc.subject Virtual musealization es_ES
dc.title Documenting Paintings with Gigapixel Photography es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/jimaging7080156 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV-VIN//SP20180066//Captura fotográfica de resolución gigapixel para la documentación y divulgación del patrimonio pictórico/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/UPV//PAID-06-18/ es_ES
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Cabezos Bernal, PM.; Rodríguez Navarro, P.; Gil Piqueras, T. (2021). Documenting Paintings with Gigapixel Photography. Journal of imaging. 7(8):1-20. https://doi.org/10.3390/jimaging7080156 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/jimaging7080156 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 20 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 7 es_ES
dc.description.issue 8 es_ES
dc.identifier.eissn 2313-433X es_ES
dc.identifier.pmid 34460792 es_ES
dc.identifier.pmcid PMC8404936 es_ES
dc.relation.pasarela S\454456 es_ES
dc.contributor.funder UNIVERSIDAD POLITECNICA DE VALENCIA es_ES
dc.contributor.funder Universitat Politècnica de València es_ES


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