ESTIMATING THE CRAMER-RAO BOUND FOR ASTRONOMICAL OBSERVATIONS - APPLICATION TO THE RICHARDSON-LUCY ALGORITHM

This work addresses the problem of assigning confidence intervals to r estored data obtained by applying the Richardson-Lucy algorithm to ast ronomical observations. The proposed solution is to estimate the Crame r-Rao bound, which describes the minimum obtainable mean square error associated with a given estimate of a parameter. This paper presents a compact method for describing the bound for Richardson-Lucy estimates . It was developed based on previously described bounds for linear res toration techniques such as Wiener filter estimates. Both one- and two -dimensional examples are presented.