Constrained iterative deconvolution using a conjugate gradient algorithm

In this paper the problem of contrained deconvolution is related to the minimization of a functional. By applying the conjugate gradient algorithm of optimization theory to this minimization an efficient iterative algorithm for deconvolution is developed. This algorithm is then extended to perform constrained deconvolution and the performance of the new algorithms is compared with other published algorithms.