  Poisson wavelets are a powerful tool in analysis of spherical signals. In
order to have a deeper characterization of them, we compute their uncertainty
product, a quantity introduced for the first time by Narcowich and Ward
in~\cite{NW96} and used to measure the trade-off between the space and
frequency localization of a function. Surprisingly, the uncertainty product of
Poisson wavelets tends to the minimal value in some limiting cases. This shows
that in the case of spherical functions, not only Gauss kernel has this
property.
