Anglia Ruskin Research Online (ARRO)
Browse
Alvaro_2017.pdf (8.03 MB)

Robust colour constancy in red-green dichromats

Download (8.03 MB)
journal contribution
posted on 2023-07-26, 14:16 authored by Leticia Álvaro, João M. M. Linhares, Humberto Moreira, Julio Lillo, Sérgio M. C. Nascimento
Colour discrimination has been widely studied in red-green (R-G) dichromats but the extent to which their colour constancy is affected remains unclear. This work estimated the extent of colour constancy for four normal trichromatic observers and seven R-G dichromats when viewing natural scenes under simulated daylight illuminants. Hyperspectral imaging data from natural scenes were used to generate the stimuli on a calibrated CRT display. In experiment 1, observers viewed a reference scene illuminated by daylight with a correlated colour temperature (CCT) of 6700K; observers then viewed sequentially two versions of the same scene, one illuminated by either a higher or lower CCT (condition 1, pure CCT change with constant luminance) or a higher or lower average luminance (condition 2, pure luminance change with a constant CCT). The observers’ task was to identify the version of the scene that looked different from the reference scene. Thresholds for detecting a pure CCT change or a pure luminance change were estimated, and it was found that those for R-G dichromats were marginally higher than for normal trichromats regarding CCT. In experiment 2, observers viewed sequentially a reference scene and a comparison scene with a CCT change or a luminance change above threshold for each observer. The observers’ task was to identify whether or not the change was an intensity change. No significant differences were found between the responses of normal trichromats and dichromats. These data suggest robust colour constancy mechanisms along daylight locus in R-G dichromacy.

History

Refereed

  • Yes

Volume

12

Issue number

6

Page range

e0180310

Publication title

PLOS ONE

ISSN

1932-6203

Publisher

Public Library of Science

File version

  • Published version

Language

  • eng

Legacy posted date

2018-02-27

Legacy creation date

2018-02-27

Legacy Faculty/School/Department

ARCHIVED Faculty of Science & Technology (until September 2018)

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC