Abstract

In this paper we investigate how the method of convex projections for image restoration behaves in the presence of noise. We also introduce and test a new noise-smoothing procedure in which the restored image is forced to lie within a certain L2 distance of the noisy data. We show that, in the presence of noise, restoration by convex projections is superior to the Gerchberg-Papoulis method.

© 1983 Optical Society of America

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