Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/51255

TítuloVisual sensitivity to color errors in images of natural scenes
Autor(es)Aldaba, Mikel A.
Linhares, João M. M.
Pinto, Paulo Daniel Araújo
Nascimento, Sérgio M. C.
Amano, Kinjiro
Foster, David H.
Palavras-chaveColor differences
Color reproduction
Color science
Complex images
Natural scenes
Data1-Mai-2006
EditoraCambridge University Press
RevistaVisual Neuroscience
Resumo(s)Simple color-difference formulae and pictorial images have traditionally been used to estimate the visual impact of color errors introduced by image-reproduction processes. But the limited gamut of RGB cameras constrains such analyses, particularly of natural scenes. The purpose of this work was to estimate visual sensitivity to color errors introduced deliberately into pictures synthesized from hyperspectral images of natural scenes without gamut constraints and to compare discrimination thresholds expressed in CIELAB and S-CIELAB color spaces. From each original image, a set of approximate images with variable color errors were generated and displayed on a calibrated RGB color monitor. The threshold for perceptibility of the errors was determined in a paired-comparison experiment. In agreement with previous studies, it was found that discrimination between original and approximate images needed on average a CIELAB color difference ΔE ab * of about 2.2. Although a large variation of performance across the nine images tested was found when errors were expressed in CIELAB units, little variation was obtained when they were expressed in S-CIELAB units.
TipoArtigo
URIhttps://hdl.handle.net/1822/51255
DOI10.1017/S0952523806233467
ISSN0952-5238
Arbitragem científicayes
AcessoAcesso restrito UMinho
Aparece nas coleções:CDF - OCV - Artigos/Papers (with refereeing)

Ficheiros deste registo:
Ficheiro Descrição TamanhoFormato 
mikel final.pdf
Acesso restrito!
189,73 kBAdobe PDFVer/Abrir

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID