Galaxies are arranged in interconnected walls and filaments
forming a cosmic web encompassing huge, nearly empty, regions
between the structures. Many statistical methods have been
proposed in the past in order to describe the galaxy distribution
and discriminate the different cosmological models. We present in
this paper preliminary results relative to the use of new
statistical tools using the 3D \`a trous algorithm, the 3D
ridgelet transform and the 3D beamlet transform. We show that such
multiscale methods produce a new way to measure in a coherent and
statistically reliable way the degree of clustering,
filamentarity, sheetedness, and voidedness of a dataset.
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