  The Vera C. Rubin Observatory Wide-Fast Deep (WFD) sky survey will reach
unprecedented surface brightness depths over tens of thousands of square
degrees. Surface brightness photometry has traditionally been a challenge.
Current algorithms which combine object detection with sky estimation
systematically over-subtract the sky, biasing surface brightness measurements
at the faint end and destroying or severely compromising low surface brightness
light. While it has recently been shown that properly accounting for undetected
faint galaxies and the wings of brighter objects can in principle recover a
more accurate sky estimate, this has not yet been demonstrated in practice.
Obtaining a consistent spatially smooth underlying sky estimate is particularly
challenging in the presence of representative distributions of bright and faint
objects. In this paper we use simulations of crowded and uncrowded fields
designed to mimic Hyper Suprime-Cam data to perform a series of tests on the
accuracy of the recovered sky. Dependence on field density, galaxy type and
limiting flux for detection are all considered. Several photometry packages are
utilised: Source Extractor, Gnuastro, and the LSST Science Pipelines. Each is
configured in various modes, and their performance at extreme low surface
brightness analysed. We find that the combination of the Source Extractor
software package with novel source model masking techniques consistently
produce extremely faint output sky estimates, by up to an order of magnitude,
as well as returning high fidelity output science catalogues.
