Asymmetries in blue-yellow color perception and in the color of 'the dress'

Abstract

The perception of color poses daunting challenges, because the light spectrum reaching the eye depends on both the reflectance of objects and the spectrum of the illuminating light source. Solving this problem requires sophisticated inferences about the properties of lighting and surfaces, and many striking examples of 'color constancy' illustrate how our vision compensates for variations in illumination to estimate the color of objects (for example [1-3]). We discovered a novel property of color perception and constancy, involving how we experience shades of blue versus yellow. We found that surfaces are much more likely to be perceived as white or gray when their color is varied along bluish directions, compared with equivalent variations along yellowish (or reddish or greenish) directions. This selective bias may reflect a tendency to attribute bluish tints to the illuminant rather than the object, consistent with an inference that indirect lighting from the sky and in shadows tends to be bluish. The blue-yellow asymmetry has striking effects on the appearance of images when their colors are reversed, turning white to yellow and silver to gold, and helps account for the variation among observers in the colors experienced in 'the dress' image that recently consumed the internet. Observers variously describe the dress as blue-black or white-gold, and this has been explained by whether the dress appears to be in direct lighting or shade (for example [5]). We show that these individual differences and potential lighting interpretations also depend on the special ambiguity of blue, for simply reversing the image colors causes almost all observers to report the lighter stripes as yellowish.

Figure 1

Examples of blue-yellow asymmetries in images. A) Colors of a positive image and its negatives. The negative on the left appears less saturated than the adjacent original, and this is due to inversion of the image hues (3^rd image) and not the luminance (4^th image). B) The perceived color differences in these images persist when the pixels are scrambled or C) when only the average chromaticity is displayed, and thus do not depend on familiarity or scene cues. D) Further examples of images with chromatic contrast inverted. The steel-gray vessels (left) change to bronze (right), and F) silver coins (left) turn to gold (right). E) In the dress, stripes that different observers variously perceived as white or blue in the original image (left) become unambiguous shades of yellow (right). G) When the color saturation is amplified, increasing blueness is attributed primarily to biased lighting (left), but increased yellowness is attributed to the object (right) (see also Figures S1 and S2). Figure 1A reproduced with permission from Anjali Webster. Figure 1E reproduced with permission from Cecilia Bleasdale.