Spatiochromatic Properties of Natural Images and Human Vision

Abstract

The human visual system shows a relatively greater response to low spatial frequencies of chromatic spatial modulation than to luminance spatial modulation. However, previous work has shown that this differential sensitivity to low spatial frequencies is not reflected in any differential luminance and chromatic content of general natural scenes. This is contrary to the prevailing assumption that the spatial properties of human vision ought to reflect the structure of natural scenes. Now, colorimetric measures of scenes suggest that red-green (and perhaps blue-yellow) color discrimination in primates is particularly suited to the encoding of specific scenes: reddish or yellowish objects on a background of leaves. We therefore ask whether the spatial, as well as chromatic, properties of such scenes are matched to the different spatial-encoding properties of color and luminance modulation in human vision. We show that the spatiochromatic properties of a wide class of scenes, which contain reddish objects (e.g., fruit) on a background of leaves, correspond well to the properties of the red-green (but not blue-yellow) systems in human vision, at viewing distances commensurate with typical grasping distance. This implies that the red-green system is particularly suited to encoding both the spatial and the chromatic structure of such scenes.

Evolution of colour vision in mammals

“…In recent years, a number of computational models of colour vision have been employed to test whether the primate M/L pigments are well suited to underlie the discrimination of fruits embedded in foliage. The consistent answer is that they are (Osorio & Vorobyev 1996;Regan et al 2001;Parraga et al 2002). However, model computations also show that there are other classes of critical behaviours, for example discrimination of edible foliage or of variations in skin coloration, which would be similarly well served by the M/L dimension of primate colour vision Changizi et al 2006).…”

Escape Distance in Ground-Nesting Birds Differs with Individual Level of Camouflage

“…Predicted cone catch values for each predator visual system were modelled from digital images after a transformation from camera to animal color space following a widely used mapping technique (Párraga et al 2002;Pike 2010;Troscianko and Stevens 2015). Cone catch images (32-bits/channel) were used for all image processing, for each predatory visual system.…”

Disruptive coloration, crypsis and edge detection in early visual processing

“…We transformed the camera's red (R), green (G), blue (B) data to a bird-specific colour space using a polynomial mapping method (Párraga et al 2002;Párraga 2003;Westland & Ripamonti 2004;Stevens et al in press b). We used the European starling (Sturnus vulgaris) as the model (Hart et al 1998), because the cone sensitivities are typical for passerine birds (Hart 2001), identified as the major predators in our study system.…”