Image restoration using nonlinear optimization techniques with a knowledge-based constraint

Richard A. Carreras

doi:10.1117/12.162000

9 November 1993 Image restoration using nonlinear optimization techniques with a knowledge-based constraint

Richard A. Carreras

Proceedings Volume 2029, Digital Image Recovery and Synthesis II; (1993) https://doi.org/10.1117/12.162000
Event: SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, 1993, San Diego, CA, United States

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.

Citation Download Citation

Richard A. Carreras "Image restoration using nonlinear optimization techniques with a knowledge-based constraint", Proc. SPIE 2029, Digital Image Recovery and Synthesis II, (9 November 1993); https://doi.org/10.1117/12.162000

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