  We present an algorithm capable of detecting diffuse, dim sources of any size
in an astronomical image. These sources often defeat traditional methods for
source finding, which expand regions around points of high intensity. Extended
sources often have no bright points and are only detectable when viewed as a
whole, so a more sophisticated approach is required. Our algorithm operates at
all scales simultaneously by considering a tree of nested candidate bounding
boxes, and inverts a hierarchical Bayesian generative model to obtain the
probability of sources existing at given locations and sizes. This model
naturally accommodates the detection of nested sources, and no prior knowledge
of the distribution of a source, or even the background, is required. The
algorithm scales nearly linear with the number of pixels making it feasible to
run on large images, and requires minimal parameter tweaking to be effective.
We demonstrate the algorithm on several types of astronomical and artificial
images.
