  In cosmic-ray physics, large field of view experiments are triggered by a
number of signals laying on different angular scales: point-like and extended
gamma-ray sources, diffuse emissions, as well as large and intermediate scale
cosmic-ray anisotropies. The separation of all these contributions is crucial,
mostly when they overlap with each other. Needlets are a form of spherical
wavelets that have recently drawn a lot of attention in the cosmological
literature, especially in connection with the analysis of CMB data. Needlets
enjoy a number of important statistical and numerical properties which suggest
that they can be very effective in handling cosmic-ray and gamma-ray data
analysis. An application of needlets to astroparticle physics is shown here. In
particular, light will be thrown on how useful they might be for estimating
background and foreground contributions. Since such an estimation is expected
to be optimal or nearly-optimal in a well-defined mathematical sense, needlets
turn out to be a powerful method for unbiased point-source detections. In this
paper needlets were applied to two distinct simulated datasets, for satellite
and EAS array experiments, both large field of view telescopes. Results will be
compared to those achievable with standard analysis tecniques in any of these
cases.
