Neighboring chromaticity influences how white a surface looks

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.This work was supported by the Portuguese Foundation for Science and Technology (FCT) in the framework of the Strategic Funding UID/ FIS/04650/2019