An iterative method for restoring noisy blurred images

This paper introduces a new iterative image restoration method which is capable of restoring noisy, blurred images by incorporating a priori knowledge about the image and noise statistics into the iterative procedure. The iteration equation consists of a prediction part which is based on a noncausal image model description and an innovation part which is weighted by a gain factor. The gain is computed using a linear MSE optimization procedure and is updated at each step of the iteration. This image restoration scheme can be interpreted as an iterative procedure with a statistical constraint on the image data.