Representing 2D digital images through a normalized measure of redundancy

This paper presents a representational model in which spatial information is analyzed by multiple filters, each of which is sensitive to patterns that contain spatial frequencies in a restricted range. The model bases its responses on only those filters sensitive to significant structures in the image. Spatial structures are described at their best scales as given by a novel normalized redundancy approach based on the intrinsic redundancy of natural scenes.