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How good are RGB cameras retrieving colors of natural scenes and paintings? — a study based on hyperspectral imaging

2020-11-01Journal article Open access
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dc.contributor.authorLinhares, João M. M.
dc.contributor.authorMonteiro, José A. R.
dc.contributor.authorBailão, Ana
dc.contributor.authorCardeira, Liliana
dc.contributor.authorKondo, Taisei
dc.contributor.authorNakauchi, Shigeki
dc.contributor.authorPicollo, Marcello
dc.contributor.authorCucci, Costanza
dc.contributor.authorCasini, Andrea
dc.contributor.authorStefani, Lorenzo
dc.contributor.authorNascimento, Sérgio Miguel Cardoso
dc.date.accessioned2021-04-13T18:30:49Z
dc.date.available2021-04-13T18:30:49Z
dc.date.issued2020-11-01
dc.description.abstractRGB digital cameras (RGB) compress the spectral information into a trichromatic system capable of approximately representing the actual colors of objects. Although RGB digital cameras follow the same compression philosophy as the human eye (OBS), the spectral sensitivity is different. To what extent they provide the same chromatic experiences is still an open question, especially with complex images. We addressed this question by comparing the actual colors derived from spectral imaging with those obtained with RGB cameras. The data from hyperspectral imaging of 50 natural scenes and 89 paintings was used to estimate the chromatic differences between OBS and RGB. The corresponding color errors were estimated and analyzed in the color spaces CIELAB (using the color difference formulas ∆E* ab and CIEDE2000), Jzazbz, and iCAM06. In CIELAB the most frequent error (using ∆E* ab) found was 5 for both paintings and natural scenes, a similarity that held for the other spaces tested. In addition, the distribution of errors across the color space shows that the errors are small in the achromatic region and increase with saturation. Overall, the results indicate that the chromatic errors estimated are close to the acceptance error and therefore RGB digital cameras are able to produce quite realistic colors of complex scenarios.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/s20216242pt_PT
dc.identifier.eid85094969680
dc.identifier.issn1424-8220
dc.identifier.pmcPMC7663052
dc.identifier.pmid33139611
dc.identifier.urihttp://hdl.handle.net/10400.14/32549
dc.identifier.wos000593555500001
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.relationPhysics Center of Minho and Porto Universities
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectChromatic errorspt_PT
dc.subjectColor differencept_PT
dc.subjectHyperspectral imagingpt_PT
dc.subjectNatural scenespt_PT
dc.subjectNumber of colorspt_PT
dc.subjectPaintingspt_PT
dc.titleHow good are RGB cameras retrieving colors of natural scenes and paintings? — a study based on hyperspectral imagingpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitlePhysics Center of Minho and Porto Universities
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04650%2F2020/PT
oaire.citation.endPage14pt_PT
oaire.citation.issue21pt_PT
oaire.citation.startPage1pt_PT
oaire.citation.titleSensors (Switzerland)pt_PT
oaire.citation.volume20pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameMaciel Linhares
person.familyNameBailao
person.familyNameNakauchi
person.familyNamePicollo
person.familyNameCucci
person.familyNameNascimento
person.givenNameJoão Manuel
person.givenNameAna
person.givenNameShigeki
person.givenNameMarcello
person.givenNameCostanza
person.givenNameSérgio
person.identifierM-7020-2013
person.identifier1000000252320
person.identifier.ciencia-idED11-ED0C-E711
person.identifier.ciencia-id4F14-C58B-E838
person.identifier.ciencia-id6D1A-818C-5BA9
person.identifier.ciencia-idBA1D-3C4C-51D8
person.identifier.orcid0000-0001-9197-5134
person.identifier.orcid0000-0002-2652-0843
person.identifier.orcid0000-0002-4954-6915
person.identifier.orcid0000-0003-1012-6048
person.identifier.orcid0000-0001-8534-7465
person.identifier.orcid0000-0002-2503-9003
person.identifier.ridT-1727-2019
person.identifier.ridH-1594-2018
person.identifier.scopus-author-id15022608200
person.identifier.scopus-author-id55328290800
person.identifier.scopus-author-id7004613700
person.identifier.scopus-author-id6701920144
person.identifier.scopus-author-id6508364267
person.identifier.scopus-author-id7003805778
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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