Always-Convergent Iterative Noise Removal and Deconvolution for Image Data

Abstract

Linear filtering techniques currently used for the restoration of noisy, blurred or otherwise degraded image data are discussed and new techniques related to the iterative techniques of Morrison and van Cittert are developed and implemented. Programs written for the implementation are discussed in the appendices. It is shown that the new techniques are convergent for any system response function, and they are applied to the task of restoring a severely blurred image.