Image statistics and the perception of surface qualities

Abstract

The world is full of surfaces, and by looking at them we can judge their material qualities. Properties such as colour or glossiness can help us decide whether a pancake is cooked, or a patch of pavement is icy. Most studies of surface appearance have emphasized textureless matte surfaces, but real-world surfaces, which may have gloss and complex mesostructure, are now receiving increased attention. Their appearance results from a complex interplay of illumination, reflectance and surface geometry, which are difficult to tease apart given an image. If there were simple image statistics that were diagnostic of surface properties it would be sensible to use them. Here we show that the skewness of the luminance histogram and the skewness of sub-band filter outputs are correlated with surface gloss and inversely correlated with surface albedo (diffuse reflectance). We find evidence that human observers use skewness, or a similar measure of histogram asymmetry, in making judgements about surfaces. When the image of a surface has positively skewed statistics, it tends to appear darker and glossier than a similar surface with lower skewness, and this is true whether the skewness is inherent to the original image or is introduced by digital manipulation. We also find a visual after-effect based on skewness: adaptation to patterns with skewed statistics can alter the apparent lightness and glossiness of surfaces that are subsequently viewed. We suggest that there are neural mechanisms sensitive to skewed statistics, and that their outputs can be used in estimating surface properties.

Perceptual transparency from image deformation

“…In many cases, proper recovery of many materialrelated physical parameters solely from the available sensory information is computationally difficult. Thus, it has been suggested that the mechanism for material perception heuristically uses simple stimulus features correlated with the physical material properties under a range of natural environments (25,28,29). In agreement with this idea, our present findings indicate that the mechanism for material perception is sensitive to the presence and absence of specific ranges of spatiotemporal frequency components in the image deformation flow.…”

Optimal sampling of visual information for lightness judgments

“…Second, the findings illustrate that the visual system might sometimes use simple and unexpected strategies to optimize its solutions to perceptual problems (40,41). In our case, the lightness of the object is better estimated by the brighter regions of the object and oversampling the brighter parts is thus a good heuristic to estimate the lightness of the object.…”

Surface gloss and color perception of 3D objects

“…and whether the visual system extracts information carried by specular highlights~Beck, 1964; Hurlbert et al, 1989;Yang & Maloney, 2001!. Not much is known about the interaction of color appearance and the material from which an object is made; only a few studies examine this question in the more restricted domain of lightness perception~Nishida & Shinya, 1998;Todd et al, 2004;Motoyoshi et al, 2007!. We return to the relation between our work and this literature in the discussion.…”