Surface segmentation based on the luminance and color statistics of natural scenes.

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.