Bayesian deconvolution with prior knowledge of object location: Applications to ground-based planetary images

In this paper we present a Bayesian method to deconvolve images when the location of the objects in the image is known in advance. This knowledge of location is incorporated into the prior model via a labeling process. An iterative method is proposed to find the maximum a posteriori estimator of the image. The method was tested on both synthetic images and ground-based CCD images of Saturn with very encouraging results.