  We present a new method of image cleaning for imaging atmospheric Cherenkov
telescopes. The method is based on the utilization of wavelets to identify
noise pixels in images of gamma-ray and hadronic induced air showers. This
method selects more signal pixels with Cherenkov photons than traditional image
processing techniques. In addition, the method is equally efficient at
rejecting pixels with noise alone. The inclusion of more signal pixels in an
image of an air shower allows for a more accurate reconstruction, especially at
lower gamma-ray energies that produce low levels of light. We present the
results of Monte Carlo simulations of gamma-ray and hadronic air showers which
show improved angular resolution using this cleaning procedure. Data from the
Whipple Observatory's 10-m telescope are utilized to show the efficacy of the
method for extracting a gamma-ray signal from the background of hadronic
generated images.

Astrophysics