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Proceedings Paper

Image restoration using nonlinear optimization techniques with a knowledge-based constraint
Author(s): Richard A. Carreras
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Paper Abstract

An image restoration problem will be formulated in the context of nonlinear programming using the conjugate gradient algorithm. The formulation of the objective function used in the conjugate gradient routine is presented. Situations may occur when there is a great deal already known about a certain object of interest which have been optically blurred because of the atmosphere or system imperfections. This paper shows a new and innovative way to incorporate a priori, perfect, partial knowledge of an object into the nonlinear optimization procedure. The topics discussed include the steps which led to the development of this procedure, the incorporation of the a priori knowledge into the nonlinear optimization problem, an analytical, mathematical approach which shows how the improvement should occur, and finally, data from simulated results which demonstrate the improvement using the developed diagnostic metrics.

Paper Details

Date Published: 9 November 1993
PDF: 18 pages
Proc. SPIE 2029, Digital Image Recovery and Synthesis II, (9 November 1993); doi: 10.1117/12.162000
Show Author Affiliations
Richard A. Carreras, Air Force Phillips Lab. (United States)

Published in SPIE Proceedings Vol. 2029:
Digital Image Recovery and Synthesis II
Paul S. Idell, Editor(s)

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