Induction operators for a computational colour-texture representation

The aim of this paper is to outline a perceptual approach to a computational colourtexture representation based on some colour induction phenomena. The extension of classical grey level methods for texture processing to the RGB channels of the corresponding colour texture is not the best solution to simulate human perception. Chromatic induction mechanisms of the human visual system, that has been widely studied in psychophysics, play an important role when looking at scenes where the spatial frequency is high as it occurs on texture images. Besides others, chromatic induction includes two complementary effects: chromatic assimilation and chromatic contrast. While the former has been measured by Wandell et al. in [1] and extended to computer vision by Petrou et al. in [2] as a perceptual blurring, some aspects on the last one still remain to be measured, but it has to be a computational operator that simulates the contrast induction phenomenon performing a perceptual sharpening that preserves the structural properties of the texture. Applying both, the perceptual sharpening and the perceptual blurring, we propose to build a tower of images as an induction front-end that can be the basis of a perceptual representation of colour textures.