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Fuhui Long, Dale Purves; A probabilistic explanation of simultaneous brightness contrast. Journal of Vision 2002;2(7):366. doi: https://doi.org/10.1167/2.7.366.
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© ARVO (1962-2015); The Authors (2016-present)
A growing body of evidence suggests that visual perception is generated according to the probabilistic relationship between the components of retinal images and their possible physical sources. We have further explored this idea by asking whether simultaneous brightness contrast effects can be explained by the statistical relationship between the physical sources of the light reaching the retina and the corresponding luminance values in the retinal image. To this end we first created a database of spectral returns (radiances) based on the interaction of average daylight (CIE D65) at 500 different levels of light intensity with 200 achromatic reflectances (interpolated from 6 standard achromatic reflectances of Macbeth ColorChecker). A database of luminances was then created by converting each of the 100,000 spectral returns obtained in this way into an RGB value using the standard CIE conversion. We then used the luminance database to create standard and ‘articulated’ brightness contrast stimuli. An analysis of the probability distributions of the possible illumination and reflectance values that could have generated the stimuli showed that: 1) the illumination of a gray patch with a dark surround is likely to be less intense than the illumination of the same patch in a lighter surround; 2) the illumination difference of gray patches in uniform surrounds is likely to be less than the illumination difference of the same patches in articulated surrounds. Thus on solely empirical grounds, these probability distributions predict that a gray patch with a darker surround will look brighter than the same patch on a lighter surround, and that the articulated version will generate a stronger perceptual effect. The significance of this work is to demonstrate that the effects of standard brightness contrast stimuli can be rationalized on the basis of the probability distributions of the sources derived from a contrived but nevertheless plausible database of visual ‘scenes’.
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