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In this issue

In this issue We open this issue with an article about the crispening effect and how well different color difference metrics predict this effect. Crispening is an increase in the magnitude of a perceived difference when two samples are viewed on a background similar to the lightness (or chromaticity) of the objects themselves, as compared to the perceived difference when viewing the two samples on a background quite different from the samples. In “The performance of advanced color difference and CAM02‐based formulas in prediction of the Crispening effect for physical samples” Hamed Karimipour and Saeideh Gorji Kandi investigate the magnitudes of the Crispening effect and the ability of various color difference metrics to predict the magnitude of the crispening effect. They found that crispening effect is increased when two stimuli have just a lightness difference instead of just chromaticity difference. They also found that some color difference metrics performed statistically better than others for the gray and the dark gray backgrounds; however, there is no significant difference for the white background.While we are talking about color appearance, Yoon Ji Cho,Li‐Chen Ou, and M. Ronnier Luo present their new models for describing four color appearance attributes. In a previous article, A Cross‐Cultural Comparison http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Color Research & Application Wiley

In this issue

Color Research & Application , Volume 42 (5) – Oct 1, 2017

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Publisher
Wiley
Copyright
© 2017 Wiley Periodicals, Inc.
ISSN
0361-2317
eISSN
1520-6378
DOI
10.1002/col.22158
Publisher site
See Article on Publisher Site

Abstract

We open this issue with an article about the crispening effect and how well different color difference metrics predict this effect. Crispening is an increase in the magnitude of a perceived difference when two samples are viewed on a background similar to the lightness (or chromaticity) of the objects themselves, as compared to the perceived difference when viewing the two samples on a background quite different from the samples. In “The performance of advanced color difference and CAM02‐based formulas in prediction of the Crispening effect for physical samples” Hamed Karimipour and Saeideh Gorji Kandi investigate the magnitudes of the Crispening effect and the ability of various color difference metrics to predict the magnitude of the crispening effect. They found that crispening effect is increased when two stimuli have just a lightness difference instead of just chromaticity difference. They also found that some color difference metrics performed statistically better than others for the gray and the dark gray backgrounds; however, there is no significant difference for the white background.While we are talking about color appearance, Yoon Ji Cho,Li‐Chen Ou, and M. Ronnier Luo present their new models for describing four color appearance attributes. In a previous article, A Cross‐Cultural Comparison

Journal

Color Research & ApplicationWiley

Published: Oct 1, 2017

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