Luminance correlations define human sensitivity to contrast resolution in natural images.
Luminance patterns encode shape and surface structure of objects in our environment. Humans can detect gradations of 1%-2% of background luminance. Is this level of sensitivity to luminance gradations (contrast) determined by the amount of ecologically meaningful information available in natural scenes? In the first experiment, subjects discriminated natural images I from their "posterized" versions I(n), in which the number of luminance gradations was reduced to n. In the second experiment, amplified residual images I(res)(n) infinity I - I(n) were discriminated from white-noise images, which lack any luminance correlations and thus information content. Performance in the two experiments matched remarkably well. Furthermore, as a function of n, the signal detected in both experiments was well fitted by the mutual information between nearby image pixels in the residual image I(res)(n). This suggests that human sensitivity to luminance contrast is optimized to extract ecologically useful information encoded by the luminance patterns of natural scenes.
Petrov
Yury
Y
The Smith-Kettlewell Eye Research Institute, 2318 Fillmore Street, San Francisco, California, 94115, USA. yury@ski.org
D001185:Artificial Intelligence; D003198:Computer Simulation; D004192:Discrimination, Psychological / Q000502:physiology*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D014796:Visual Perception / Q000502:physiology*