LUT and multilevel Brownian Retinex colour correction

Retinex, a model of human color vision suitable for unsupervised chromatic equalization, due to Land and McCann, is receiving a renewed interest after several years. Different versions have been developed so far, and it has been used for various applications. Most of the implementations skip the classical random paths approach because of the high frequency chromatic noise it introduces. To solve the noise problem, avoiding the increase of paths number and without substituting the random paths approach, we present in this paper two new retinex versions: one based on a look-up table transformation, and another based on multilevel image decomposition. These versions strongly decrease the dependency of the computed pixel value on the path randomness, eliminating in this way a great part of the chromatic noise.