Simultaneous Image Identification And Restoration Using The Em-Algorithm

In many situations of interest the degradation an image has suffered is unknown prior to the restoration process. For this reason the point-spread function of the degrading system has to be estimated directly from the available noisy blurred image. We present a maximum likelihood approach to this image identification problem, and employ the computationally efficient and flexible EM-algorithm to solve the resulting highly nonlinear optimization problem. This approach results in an efficient iterative algorithm, which simultaneously identifies and restores noisy blurred images.