An optimal neuron evolution algorithm for the restoration
of linearly distorted Images is presented in this paper. The proposed
algorithm is motivated by the symmetric positive-definite quadratic programming
structure inherent in restoration. Theoretical analysis and experimental
results show that the algorithm not only significantly increases
the convergence rate of processing, hut also produces good restoration
results. In addition, the algorithm provides a genuine parallel processing
structure which ensures computationally feasible spatial domain image
restoration
