In the last decade, multiscale techniques for gray-level texture analysis have been intensively studied. In this paper, we aim on extending these techniques to color images. We introduce wavelet energy-correlation signatures and we derive the transformation of these signatures upon linear color space transformations. Classification experiments demonstrate that the wavelet correlation features contain more information than the intensity or the energy features of each color plane separately. The influence of image representation in color space is evaluated.