Abstract

Deconvolution is an important problem in many branches of physics and engineering, and many different algorithms have been considered for deconvolving two signals. Iterative algorithms based on the method of successive approximations have become popular for signal deconvolution because of the flexibility that they allow for the incorporation of signal constraints into the restoration. One of the limitations with these iterative algorithms, however, is that they achieve only a linear rate of convergence. In this paper an accelerated iterative deconvolution algorithm is presented that is based on the idea of updating the observation equation after each iteration. With this approach it is shown that the modified iterative algorithm achieves a quadratic rate of convergence. Although with this new algorithm there is a significant increase in the convergence rate, the incorporation of signal constraints into the iteration is more difficult than with the algorithms based on the method of successive approximation.

© 1987 Optical Society of America

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