  The standard imaging algorithm for interferometric radio data, CLEAN, is
optimal for point source observations, but suboptimal for diffuse emission.
Recently, RESOLVE, a new Bayesian algorithm has been developed, which is ideal
for extended source imaging. Unfortunately, RESOLVE is computationally very
expensive. In this paper we present fastRESOLVE, a modification of RESOLVE
based on an approximation of the interferometric likelihood that allows us to
avoid expensive gridding routines and consequently gain a factor of roughly 100
in computation time. Furthermore, we include a Bayesian estimation of the
measurement uncertainty of the visibilities into the imaging, a procedure not
applied in aperture synthesis before. The algorithm requires little to no user
input compared to the standard method CLEAN while being superior for extended
and faint emission. We apply the algorithm to VLA data of Abell 2199 and show
that it resolves more detailed structures.
