Restoration from partially-known blur using an expectation-maximization algorithm

In this paper we address the problem of image restoration when the point-spread function (PSF) of the imaging process is not known exactly, a situation which arises regularly in practice. The algorithm based on the expectation-maximization (EM) algorithm is proposed which has the capability to identify the unknown statistics of the image and the image-dependent noise while restoring the image. The convergence properties of the resulting estimators are examined.