Abstract
In this paper a class of iterative image restoration algorithms is derived based on a representation theorem for the generalized inverse of a matrix. These algorithms exhibit a first or higher order of convergence and some of them consist of an on-line and an off-line computational part. The conditions of convergence and the rate of convergence of these algorithms are derived. A faster rate of convergence can be achieved by increasing the computational load. The algorithms can be applied to the restoration of signals of any dimensionality. Iterative restoration algorithms that have appeared in the literature represent special cases of the class of algorithms described here.
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