MAXIMUM A-POSTERIORI RESTORATION OF BLURRED IMAGES USING SELF-ORGANIZATION

We use the ''magic TV'' network with the maximum a posteriori (MAP) cr iterion to restore a space-dependent blurred image. This network provi des a unique topological invariance mechanism that facilitates the ide ntification of such space-dependent blur. Instead of using parametric modeling of the underlying blurred image, we use this mechanism to acc omplish the restoration. The restoration is reached by a self-organizi ng evolution in the network, where the weight matrices are adapted to approximate the blur functions. The MAP criterion is used to indicate the goodness of the approximation and to direct the evolution of the n etwork. (C) 1998 SPIE and IS&T. [S1017-9909(98)01001-0].