title: Surface segmentation based on the luminance and color statistics of natural scenes.
abstract: The luminance and color of surfaces in natural scenes are relatively independent under certain linear transformations, with the luminance of a surface providing little information about the color of that surface, and vice versa. However, differences in luminance between two locations in a natural scene remain strongly associated with differences in color. We used the statistics of the spatiochromatic structure of natural scenes as the priors for a Bayesian model that decides whether or not two points within an image fall on the same surface. This model provides a biologically plausible algorithm for surface segmentation that models observer segmentations well.
authors.affiliation: Department of Psychology, Box 0109, 9500 Gilman Drive, University of California, San Diego, San Diego, California 92093-0109, USA. fine@salk.edu
authors.forename: Ione
authors.initials: I
authors.lastname: Fine
authors.forename: Donald I A
authors.initials: DI
authors.lastname: MacLeod
authors.forename: Geoffrey M
authors.initials: GM
authors.lastname: Boynton
mesh_terms: D003116:Color; D003118:Color Perception / Q000502:physiology*; D006801:Humans; D008029:Lighting; D008954:Models, Biological