A simple algorithm for joint blur identification and image restoration

Earlier work on blur identification suffers from using space-invariant image models to match space-variant (piecewise smooth) images. It is expected that an effective space-adaptive image model or estimate would improve the joint blur and image estimation. A well-known space-adaptive regularization method for image restoration is extended to solve this problem. The resulting scheme has two regularization terms, one for the image and the other for the blur. Very good performance is observed even though no stringent assumption about the structure of the underlying blur operator is made. The computational overhead for blur identification is less than the computational load required for regularized image restoration when the blur operator is exactly known.