The estimation of the intensity function of a Poisson-driven shot-nois
e process is addressed using a regularization technique, where the dat
a is modeled as a signal term plus a signal-dependent noise term. A ne
w data-based method for selecting a pair of regularization parameters
is presented and compared with the minimum unbiased risk method. The d
etail in the intensity function can be recovered by both methods, but
the new method does a better job at suppressing spurious oscillations.