Lightness from contrast: A selective integration model

67Citations
Citations of this article
31Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

As has been observed by Wallach (1948), perceived lightness is proportional to the ratio between the luminances of adjacent regions in simple disk-annulus or bipartite scenes. This psychophysical finding resonates with neurophysiological evidence that retinal mechanisms of receptor adaptation and lateral inhibition transform the incoming illuminance array into local measures of luminance contrast. In many scenic configurations, however, the perceived lightness of a region is not proportional to its ratio with immediately adjacent regions. In a particularly striking example of this phenomenon, called White's illusion, the relationship between the perceived lightnesses of two gray regions is the opposite of what is predicted by local edge ratios or contrasts. This paper offers a new treatment of how local measures of luminance contrast can be selectively integrated to simulate lightness percepts in a wide range of image configurations. Our approach builds on a tradition of edge integration models (Horn, 1974; Land & McCann, 1971) and contrast/filling-in models (Cohen & Grossberg, 1984; Gerrits & Vendrik 1970; Grossberg & Mingolla, 1985a, 1985b). Our selective integration model (SIM) extends the explanatory power of previous models, allowing simulation of a number of phenomena, including White's effect, the Benary Cross, and shading and transparency effects reported by Adelson (1993), as well as aspects of motion, depth, haploscopic, and Gelb induced contrast effects. We also include an independently derived variant of a recent depthful version of White's illusion, showing that our model can inspire new stimuli.

Cite

CITATION STYLE

APA

Ross, W. D., & Pessoa, L. (2000). Lightness from contrast: A selective integration model. Perception and Psychophysics, 62(6), 1160–1181. https://doi.org/10.3758/BF03212120

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free