Abstract
A new iterative algorithm is presented for restoring noisy blurred images where the point spread function (PSF) is unknown. 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) algorithm, 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. Computer simulations illustrate the new method to be very competitive in restoring noisy degraded images with unknown PSF.
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