  A probabilistic technique for the joint estimation of background and sources
with the aim of detecting faint and extended celestial objects is described.
Bayesian probability theory is applied to gain insight into the coexistence of
background and sources through a probabilistic two-component mixture model,
which provides consistent uncertainties of background and sources. A
multi-resolution analysis is used for revealing faint and extended objects in
the frame of the Bayesian mixture model. All the revealed sources are
parameterized automatically providing source position, net counts,
morphological parameters and their errors.
