Visual wetness perception based on image color statistics

Abstract

Color vision provides humans and animals with the abilities to discriminate colors based on the wavelength composition of light and to determine the location and identity of objects of interest in cluttered scenes (e.g., ripe fruit among foliage). However, we argue that color vision can inform us about much more than color alone. Since a trichromatic image carries more information about the optical properties of a scene than a monochromatic image does, color can help us recognize complex material qualities. Here we show that human vision uses color statistics of an image for the perception of an ecologically important surface condition (i.e., wetness). Psychophysical experiments showed that overall enhancement of chromatic saturation, combined with a luminance tone change that increases the darkness and glossiness of the image, tended to make dry scenes look wetter. Theoretical analysis along with image analysis of real objects indicated that our image transformation, which we call the wetness enhancing transformation, is consistent with actual optical changes produced by surface wetting. Furthermore, we found that the wetness enhancing transformation operator was more effective for the images with many colors (large hue entropy) than for those with few colors (small hue entropy). The hue entropy may be used to separate surface wetness from other surface states having similar optical properties. While surface wetness and surface color might seem to be independent, there are higher order color statistics that can influence wetness judgments, in accord with the ecological statistics. The present findings indicate that the visual system uses color image statistics in an elegant way to help estimate the complex physical status of a scene.

Color consistency in the appearance of bleached fabrics

“…The fact that people can infer the original color of bleached surfaces indicates that they can identify the chromatic changes because of the bleaching process and to some extent discount them. This is consistent with the finding that people use chromatic cues (i.e., color saturation) to perceive a surface as wet (Sawayama et al, 2017). Because the changes are interpreted as a change in the state of the material, rather than a change in the material itself, it suggests that the visual system can somehow separate the saturation increase that is owing to wetting from the intrinsic color of the surface.…”

“…There has been very little research on the perceptions of transformations that affect color. Sawayama and colleagues (Sawayama, Adelson, & Nishida, 2017) found that modifying the color distributions of photographs of natural textures can alter whether they appear to be wet or dry. Specifically, enhancing chromatic saturation while increasing darkness and glossiness tended to make dry scenes look wet.…”

Physicochemical properties of hammer‐milled yellow split pea (Pisum Sativum L.)

“…Flours were brighter when processed at 11% moisture, at 102 m/s, and at small screen aperture, though differences in brightness due to seed moisture were of small practical significance (Table ). In general, flour with higher water content is expected to reflect less light and appear darker than the same flour at lower water content (Sawayama, Adelson, & Nishida, ). However, lower brightness values were observed at lower moisture content.…”

Visual Perception of Moisture Is a Pathogen Detection Mechanism of the Behavioral Immune System

“…Firstly, we used only eight mixtures of dough as experimental stimuli, which limits the generalizability of our findings, because it is unclear whether the findings can be applied to materials other than dough. Sawayama et al (2017) demonstrated that the surface color of wet objects looks more saturated, which suggests that perceptible cues of moisture might depend on the type of material. Furthermore, the number of stimuli used in these two experiments was small, which makes it difficult to conclude if the results reflect the general characteristics of dough or characteristics specific to the stimuli.…”