Paper
30 May 2002 Contribution of local and global cone-contrasts to color appearance: a Retinex-like model
Anya C. Hurlbert, Christopher J. L. Wolf
Author Affiliations +
Proceedings Volume 4662, Human Vision and Electronic Imaging VII; (2002) https://doi.org/10.1117/12.469525
Event: Electronic Imaging, 2002, San Jose, California, United States
Abstract
Recent psychophysical experiments demonstrate that for simple configurations, colour appearance is largely determined by the ratios of within-type cone excitations (cone contrasts) between a target surface and its immediate background. Other experiments demonstrate that both the mean and variance of the cone excitations from remote surfaces may influence the colour of a target surface. The relative contribution of local and remote surfaces to the colour appearance of a centrally viewed target also depends on adaptational state and, therefore, on stimulus duration. Cone-contrast models of colour appearance that include the influence of cone excitations from local and global surfaces may be viewed as modern-day successors of the Retinex model for colour constancy. Here we describe psychophysical experiments of colour matching under simulated illumination changes, and examine the effects of the size and configuration of local and remote chromatic elements in a complex background on the colour appearance of a central target. We compare the observed colour matches with predictions from a standard Retinex model and from a modified Retinex-like model with weighting factors on the distance-order of chromatic edges.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anya C. Hurlbert and Christopher J. L. Wolf "Contribution of local and global cone-contrasts to color appearance: a Retinex-like model", Proc. SPIE 4662, Human Vision and Electronic Imaging VII, (30 May 2002); https://doi.org/10.1117/12.469525
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Cited by 6 scholarly publications.
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KEYWORDS
Colorimetry

Cones

MATLAB

RGB color model

Data modeling

Detection and tracking algorithms

Visual process modeling

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