Image restoration and identification using the EM and adaptive RAP algorithms

Abstract

A new iterative algorithm for image restoration and point spread function (PSF) estimation is presented. The method initially estimates the PSF and the original image using the Expectation Maximization (EM) method. The resulting image estimate is then refined by using the adaptive Row Action Projection (RAP) algorithms which is based on the theory of Projection Onto Convex Sets (POCS). The new implementation of the RAP algorithm can be performed efficiently in parallel and facilitates locally adaptive constraints and cycling strategies. The PSF is re-estimated using a least square technique. Computer simulations illustrate the new method to be very competitive in restoring degraded images and estimating the PSF from noisy blurred images with unknown PSF.