IMAGE-RESTORATION USING LAYERED NEURAL-NETWORKS AND HOPFIELD NETWORKS

An algorithm is developed for the restoration of an image degraded by a known two-dimensional (2-D) shift-invariant point-spread function an d corrupted with white noise. A layered neural network and the Hopfiel d network are used for the edge detection, and the restoration and smo othing of a blurred image, respectively. In particular, a layered neur al network is proposed for exact edge detection where the inputs consi st of three pixel values and a local variance in a 2-D mask. This netw ork can detect edges and suppress the noise in an image at the same ti me, and its performance is adjusted by learning. Finally, some example s are given to illustrate the utility of the proposed algorithm.