Multi-resolution filtering: an empirical method for isolating faint,
  extended emission in Dragonfly data and other low resolution images
  We describe an empirical, self-contained method to isolate faint, large-scale
emission in imaging data of low spatial resolution. Multi-resolution filtering
(MRF) uses independent data of superior spatial resolution and point source
depth to create a model for all compact and high surface brightness objects in
the field. This model is convolved with an appropriate kernel and subtracted
from the low resolution image. The halos of bright stars are removed in a
separate step and artifacts are masked. The resulting image only contains
extended emission fainter than a pre-defined surface brightness limit. The
method was developed for the Dragonfly Telephoto Array, which produces images
that have excellent low surface brightness sensitivity but poor spatial
resolution. We demonstrate the MRF technique using Dragonfly images of a
satellite of the spiral galaxy M101, the tidal debris surrounding M51, two
ultra-diffuse galaxies in the Coma cluster, and the galaxy NGC5907. As part of
the analysis we present a newly-identified very faint galaxy in the filtered
Dragonfly image of the M101 field. We also discuss variations of the technique
for cases when no low resolution data are available (self-MRF and cross-MRF).
The method is implemented in mrf, an open-source MIT licensed Python package.
