  In this paper, we propose a numerical strategy to define a multiscale
analysis for color and multicomponent images based on the representation of
data on a graph. Our approach consists in computing the graph of an image using
the psychovisual information and analysing it by using the spectral graph
wavelet transform. We suggest introducing color dimension into the computation
of the weights of the graph and using the geodesic distance as a means of
distance measurement. We thus have defined a wavelet transform based on a graph
with perceptual information by using the CIELab color distance. This new
representation is illustrated with denoising and inpainting applications.
Overall, by introducing psychovisual information in the graph computation for
the graph wavelet transform we obtain very promising results. Therefore results
in image restoration highlight the interest of the appropriate use of color
information.
