On the second order spatiochromatic structure of natural images.

We provide a theoretical analysis of some empirical facts about the second order spatiochromatic structure of natural images in color. In particular, we show that two simple assumptions on the covariance matrices of color images yield eigenvectors made by the Kronecker product of Fourier features times the triad given by luminance plus color opponent channels. The first of these assumptions is second order stationarity while the second one is commutativity between color correlation matrices. The validity of these assumptions and the predicted shape of the PCA components of color images are experimentally observed on two large image databases. As a by-product of this experimental study, we also provide novel data to support an exponential decay law of the spatiochromatic covariance between pairs of pixels as a function of their spatial distance.

Estimation of illuminants from projections on the Planckian locus.

This paper introduces a new approach for the automatic estimation of illuminants in a digital color image. The method relies on two assumptions. First, the image is supposed to contain at least a small set of achromatic pixels. The second assumption is physical and concerns the set of possible illuminants, assumed to be well approximated by black body radiators. The proposed scheme is based on a projection of selected pixels on the Planckian locus in a well chosen chromaticity space, followed by a voting procedure yielding the estimation of the illuminant. This approach is very simple and learning-free. The voting procedure can be extended for the detection of multiple illuminants when necessary. Experiments on various databases show that the performances of this approach are similar to those of the best learning-based state-of-the-art algorithms.