  We develop an improved sky background estimator which employs optimal filters
for both spatial and pixel intensity distributions. It incorporates growth of
masks around detected objects and a statistical estimate of the flux from
undetected faint galaxies in the remaining sky pixels. We test this algorithm
for underlying sky estimation and compare its performance with commonly used
sky estimation codes on realistic simulations which include detected galaxies,
faint undetected galaxies, and sky noise. We then test galaxy surface
brightness recovery using GALFIT 3, a galaxy surface brightness profile fitting
optimizer, yielding fits to S\'{e}rsic profiles. This enables robust sky
background estimates accurate at the 4 parts-per-million level. This background
sky estimator is more accurate and is less affected by surface brightness
profiles of galaxies and the local image environment compared with other
methods.
