research-article

Modeling human color perception under extended luminance levels

Authors:

Jan KautzAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 28, Issue 3

Article No.: 27, Pages 1 - 9

https://doi.org/10.1145/1531326.1531333

Published: 27 July 2009 Publication History

Abstract

Display technology is advancing quickly with peak luminance increasing significantly, enabling high-dynamic-range displays. However, perceptual color appearance under extended luminance levels has not been studied, mainly due to the unavailability of psychophysical data. Therefore, we conduct a psychophysical study in order to acquire appearance data for many different luminance levels (up to 16,860 cd/m²) covering most of the dynamic range of the human visual system. These experimental data allow us to quantify human color perception under extended luminance levels, yielding a generalized color appearance model. Our proposed appearance model is efficient, accurate and invertible. It can be used to adapt the tone and color of images to different dynamic ranges for cross-media reproduction while maintaining appearance that is close to human perception.

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Cited By

Silva MSeoane AMures OLópez AIglesias-Guitian J(2025)Exploring the effects of synthetic data generation: a case study on autonomous driving for semantic segmentationThe Visual Computer10.1007/s00371-025-03811-1Online publication date: 7-Feb-2025
https://doi.org/10.1007/s00371-025-03811-1
Vernet SDinet ETrémeau AColantoni P(2024)Experimental Protocol for Color Difference Evaluation Under Stabilized LED LightJournal of Imaging10.3390/jimaging1101000411:1(4)Online publication date: 30-Dec-2024
https://doi.org/10.3390/jimaging11010004
Hwang JBaek YKwak YHong Y(2024)Color-appearance-matched data in high-dynamic-range luminance conditionsJournal of the Optical Society of America A10.1364/JOSAA.51551641:7(1259)Online publication date: 3-Jun-2024
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Index Terms

Modeling human color perception under extended luminance levels
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
      2. Image and video acquisition
        3D imaging
  2. Computer graphics
2. Theory of computation
  1. Randomness, geometry and discrete structures
    1. Computational geometry

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Published In

cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 28, Issue 3

August 2009

750 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/1531326

Issue’s Table of Contents

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 27 July 2009

Published in TOG Volume 28, Issue 3

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Cited By

Silva MSeoane AMures OLópez AIglesias-Guitian J(2025)Exploring the effects of synthetic data generation: a case study on autonomous driving for semantic segmentationThe Visual Computer10.1007/s00371-025-03811-1Online publication date: 7-Feb-2025
https://doi.org/10.1007/s00371-025-03811-1
Vernet SDinet ETrémeau AColantoni P(2024)Experimental Protocol for Color Difference Evaluation Under Stabilized LED LightJournal of Imaging10.3390/jimaging1101000411:1(4)Online publication date: 30-Dec-2024
https://doi.org/10.3390/jimaging11010004
Hwang JBaek YKwak YHong Y(2024)Color-appearance-matched data in high-dynamic-range luminance conditionsJournal of the Optical Society of America A10.1364/JOSAA.51551641:7(1259)Online publication date: 3-Jun-2024
https://doi.org/10.1364/JOSAA.515516
Wang HWei M(2024) Characterization of Color Appearance of Self‐Luminous Highlights Under HDR Scenes, Part I: Brightness for Neutral Stimuli Color Research & Application10.1002/col.22965Online publication date: 22-Nov-2024
https://doi.org/10.1002/col.22965
Avendano Martinez AZuena JPytlarz J(2024)Evaluating the perceived brightness of chromatic stimuli with backgrounds of varying luminanceColor Research & Application10.1002/col.2294950:1(59-71)Online publication date: 13-Aug-2024
https://doi.org/10.1002/col.22949
Kubota YYoshida SInami M(2023)Apparent color picker: color prediction model to extract apparent color in photosFrontiers in Signal Processing10.3389/frsip.2023.11332103Online publication date: 9-May-2023
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Yi SJeon DSerrano AJeong SKim HGutierrez DKim M(2022)Modelling Surround‐aware Contrast Sensitivity for HDR DisplaysComputer Graphics Forum10.1111/cgf.1443941:1(350-363)Online publication date: 7-Jan-2022
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