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

摘要

This work addresses the problem of assigning confidence intervals to restored data obtained by applying the Richardson-Lucy algorithm to astronomical observations. The proposed solution is to estimate the Cramer-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 restoration techniques such as Wiener filter estimates. Both one- and two-dimensional examples are presented.