Chromatic induction effects depend, among others, on the frequency content of the observed region. Highly textured images usually show some dominant frequency information, which produces prominent chromatic induction effects when observed. As it is shown by some authors, the two chromatic induction effects, i.e., chromatic contrast and assimilation, can be computationally simulated by blurring and sharpening operators, respectively. In this article, we present a first approximation to the perceptual representation of highly textured images using a wavelet decomposition approach. Wavelet coefficients are modulated by a weighting function, which performs either assimilation or contrast at every frequency level of the image. This wavelet approach allows us to define both chromatic induction effects in a unified framework as a single mathematical operator.