Neighboring chromaticity influences how white a surface looks

Abstract

To identify surface properties independently of the illumination the visual system must make assumptions about the statistics of scenes and their illumination. Are assumptions about the intensity of the illumination independent of assumptions about its chromaticity? To find out, we asked participants to judge whether test patches within three different sets of surrounding surfaces were white or grey. Two sets were matched in terms of their maximal luminance, their mean luminance and chromaticity, and the variability in their luminance and chromaticity, but differed in how luminance and chromaticity were associated: the highest luminance was either associated with colorful surfaces or with achromatic ones. We found that test patches had to have a higher luminance to appear white when the highest luminance in the surrounding was associated with colorful surfaces. This makes sense if one considers that being colorful implies that a surface only reflects part of the light that falls on it, meaning that the illumination must have a higher luminance (a perfectly white surface reflects all of the light falling on it). In the third set, the colorful surfaces had the same luminance as in the set in which they were associated with the highest luminance, but the achromatic surfaces had a lower luminance so that the overall mean luminance was lower. Despite the constraints on the illumination being identical, test patches did not have to have as high luminance to appear white for the third set. Considering the layout of the surfaces in the surrounding revealed that test patches did have to have the same high luminance if the high luminance colorful surfaces were adjacent to the target patch. Thus, the assumptions about the possible illumination are applied locally. A possible mechanism is relying on the contrast within each type of cone: for a surface to appear white it must stimulate each of the three kinds of cones substantially more than do any neighboring surfaces.

Chromatic Anchoring of Lightness

“…It has also been found that the lightness of highly saturated chromatic colours influences the perceived chromaticity of the white-point [26,27], an observation potentially in line with the idea of chromatic anchoring. Still another study found that perceived lightness of the brightest colours was lower when the probe stimulus was surrounded by more saturated green, blue, and red colours [28]. This observation is in line with chromatic anchoring of lightness because higher saturation of green, blue, and red implies that the white-point is higher in brightness and hence the lightness scale involves higher levels of brightness.…”

“…Despite the low resolution of the colour naming measure and the minimalism of our set-up we obtained clear evidence for chromatic anchoring: While displays without chromatic anchor were almost unanimously judged white (Figure 2.a-d), those with the red and two of the blue chromatic anchors (Figure 2.e-j) were almost unanimously judged grey. These pronounced effects of chromatic anchors contrast the subtle effects of saturation on lightness judgements observed in a previous study that used a much richer, patterned display with many colours [28]. That study also used repeated measurements for each observer, which should lead to a higher signal to noise ratio compared to our single measurement per participant.…”

“…That study also used repeated measurements for each observer, which should lead to a higher signal to noise ratio compared to our single measurement per participant. Crucially, that study [28] speculated that effects of saturation might be due to observers interpreting the colours as coloured surfaces and making assumptions about the possible illumination.…”

“…Knowledge about the properties of a particular gamut can be accumulated across trials. This may explain why anchoring effects of stimulus-specific gamuts may be small [28] or even disappear [40] in repeated-measurement designs. In such studies, anchoring is compared across trials with different stimulus displays, assuming that each stimulus display should produce anchoring specific to its own gamut.…”

Near perfect visual compensation for atmospheric color distortions

“…Such an effect may be described as a uniform veil that acted in a spatially uniform manner on the image 31,32 . The model in use here was applied solely to spectral stimulus that reached the eye of the observer and did not independently consider the effect of atmospheric variations as a veil, how they could be partially discounted 33 or how the surrounding colors could impact local perception of the image 34 . Observers could use saturation as a cue to perform the task in the psychophysical experiment, but as negative‐distance images become more saturated, this cue would not provide indication of the original image.…”