WAVELETS AND THE STUDY OF THE DISTANT UNIVERSE

The large-scale distribution of galaxies in the Universe exhibits stru ctures at various scales, these so-called groups, clusters, and superc lusters of galaxies being more or less hierarchically organized. A spe cific vision model is needed in order to detect, describe, and classif y each component of this hierarchy. To do so rue have developed a mult iscale vision model based on an unfolding into a scale space allowing us to detect structures of different sizes. A discrete wavelet transfo rm is done by the a trous algorithm. The algorithm is implemented for astronomical images and also for lists of object positions, currently called catalogues in astronomical literature. Some applications on ast rophysical data of cosmological interest are briefly described: 1) inv entory procedures for galaxy counts on wide-field images, 2) processin g of X-ray cluster images, leading to the analyses of the total matter distribution, and 3) detection of large-scale structures from galaxy counts. From the analyses of n-body simulations we show that the visio n model from the wavelet transform provides a new statistical indicato r on cosmological scenarios.