Explaining brightness illusions using spatial filtering and local response normalization

Alan E. Robinson^a^,^,, Paul S. Hammon^b and Virginia R. de Sa^a
^aDepartment of Cognitive Science; ^bDepartment of Electrical and Computer Engineering;
University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0515, USA
Received 13 October 2006; revised 5 February 2007. Available online 24 April 2007.

Abstract

We introduce two new low-level computational models of brightness perception that account for a wide range of brightness illusions, including many variations on White's Effect [Perception, 8, 1979, 413]. Our models extend Blakeslee and McCourt's ODOG model [Vision Research, 39, 1999, 4361], which combines multiscale oriented difference-of-Gaussian filters and response normalization. We extend the response normalization to be more neurally plausible by constraining normalization to nearby receptive fields (models 1 and 2) and spatial frequencies (model 2), and show that both of these changes increase the effectiveness of the models at predicting brightness illusions.

Article (PDF, 813K)

Citation: Robinson, AE, Hammon, PS, & de Sa, VR. (2007). Explaining brightness illusions using spatial filtering and local response normalization. Vision Research, 47, 1631-1644.

Matlab code for the ODOG, LODOG, and FLODOG models are available on request; email Alan Robinson at the email address below.

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