Visual wetness perception based on image color statistics

Journal of Vision
Masataka SawayamaShin'ya Nishida

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 entrop...Continue Reading

Citations

Apr 28, 2018·PLoS Computational Biology·Masataka Sawayama, Shin'ya Nishida
Apr 22, 2020·Journal of Vision·Matteo ToscaniKarl R Gegenfurtner
Jun 4, 2020·Journal of Vision·Filipp SchmidtMatteo Valsecchi
Sep 11, 2019·Journal of the Optical Society of America. A, Optics, Image Science, and Vision·Hitomi OtakaIsamu Motoyoshi
Sep 17, 2019·I-Perception·Gunnar Wendt, Franz Faul
Mar 3, 2020·Frontiers in Psychology·Kazunori IwasaYuta Sakamoto
Oct 30, 2018·Journal of Vision·Alice C ChadwickRobert W Kentridge
Oct 16, 2019·Journal of Vision·Hiroaki KiyokawaTakehiro Nagai
May 14, 2020·Journal of the Optical Society of America. A, Optics, Image Science, and Vision·Taishi Masumitsu, Yoko Mizokami
Aug 4, 2021·Journal of Vision·Davit GigilashviliMarius Pedersen

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