Abstract

The problem of 2-D digital restoration of images degraded by spatially varying pointspread functions is considered. It is shown that the conjugate gradient method can be applied to this problem. This algorithm preserves the sparse matrix properties of other iterative approaches to least squares restoration but has improved convergence properties. The approximation of pointspread matrices by banded matrices is shown to improve the speed of the algorithm without significantly affecting the restoration.

© 1978 Optical Society of America

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