Explaining brightness illusions using spatial filtering and local response normalization.

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.