Understanding individual differences in color appearance of “#TheDress” based on the optimal color hypothesis

Journal article

We performed a theoretical analysis based on our optimal color hypothesis to explain why “#TheDress” image had a different color appearance for different observers (observer-dependent perception). We then carried out an experiment to test the hypothesis derived from the aforementioned theoretical analysis. In the optimal color hypothesis, the visual system picks the optimal color distribution that provides the best fit to the luminance distribution at a scene. The peak of the best-fit optimal color distribution corresponds with the illuminant's color temperature. In the theoretical analysis, we found that as the luminance level was increased the best-fit optimal color temperature changes abruptly from high to low at a specific luminance-level. Under the dark-blue (low luminance and high color temperature) illuminant the dress should appear white/gold whereas under the bright-white (high luminance and low color temperature) illuminant the dress should appear blue/black. The observer-dependent appearances of the dress may be explained by this luminance-dependent illuminant prediction. In the experiment, we used the original dress, a chromatically inverted dress, and an achromatic dress as stimuli. The observer adjusted chromaticity and luminance of a test field drawn onto the dress image so that it appeared as a full-white surface. We found that the white/gold group estimated the illuminant to be darker and bluish and the blue/black group estimated it to be brighter and yellowish. The observer's estimated illuminant was consistent with the predicted illuminant by the optimal color theory. It was newly discovered that even when the dress was achromatic, these two groups estimated the illuminant to be darker or brighter in the same way as for the original dress.

Authors: Uchikawa, K; Morimoto, T; Matsumoto, T

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Association for Research in Vision and Ophthalmology (ARVO)
• Journal: Journal of Vision
• Volume: 17
• Issue: 8
• Pages: 1-14
• Publication date: 2017-07-28
• Acceptance date: 2017-06-18
• DOI: 10.1167/17.8.10
• ISSN: 1534-7362