Photometry of crowded fields is an old theme of astronomical image
processing. Large space surveys in the UV (ultraviolet), like the GALEX
mission (135-175 nm and 170-275 nm range), confronts us again with
challenges like, very low light levels, poor resolution, variable
stray-light in background, the extended and badly known PSFs (point
spread functions), etc. However the morphological
... [Show full abstract] similitude of these UV
images to their counterparts in the visible bands, suggests that we use
all this high resolution data as the starting reference for the UV
analysis. We choose the Bayesian approach. However there is not a
straightforward way leading from the basic idea to its practical
implementation. We will describe in this paper the path which starts
with the original procedure (presented in a previous paper) and ends on
the useful one. After a brief recall on the Bayesian method, we describe
the process applied to restore from the UV images the point spread
function (PSF) and the background due to stray-light. In the end we
display the photometric performances reached for each channel and we
discuss the consequences of the imperfect knowledge of background, the
inaccuracy on object centring and on the PSF model. Results show a clear
improvement by more than 2 mag on the magnitude limit and in the
completeness of the measured objects relative to classical methods (it
corresponds to more than 75000 new objects per GALEX field, i.e. approx
25% more). The simplicity of the Bayesian approach eased the analysis as
well as the corrections needed in order to obtain a useful and reliable
photometric procedure.