Wavelets have been very successfull for many astronomical applications such as filtering, deconvolution, source detection or compression. Wavelets have however some limitations when the data present anisotropic features, so we present other multiscale methods in 2D and in 3D, such the ridgelets or the curvelets, better adapted to this kind of data. We show how to use these new 2D and 3D multiscale transforms for various cosmological applications such the analysis of the spatial distribution of galaxies or the detection of non-Gaussian signatures in the Cosmic Microwave Background.
Dr. Jean-Luc Starck, a tenured researcher at CEA/Saclay France, obtained his PhD from the University of Nice at Sophia Antipolis, France in 1992. His research has been revolving on a variety of problems related to signal processing techniques for astronomical data analysis such as filtering, deconvolution, compression, and faint source detection. Particular emphasis is given to novel techniques such as wavelet, ridgelet, curvelet and non linear multiscale methods. He has published about 100 papers and he is co-author of two textbooks in the area: - "Image and Data Analysis" by J-L. Starck, F. Murtagh and A. Bijaoui, Cambridge Univ. Press, 1998 - "Astronomical Image and Data Analysis", by J-L. Starck and F. Murtagh, Springer 2002 and 2006 Recently he has been applying these techniques to address problems of Observational Cosmology in preparation for the upcoming Plank Space Telescope mission which will be launched by ESA in 2008. For more information visit his personal web page at http://jstarck.free.fr/
