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Proceedings Paper

GA image restoration using parameters of degrading and restoring functions as genes
Author(s): Tomokazu Tamaoki; Noboru Funakubo
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Paper Abstract

In this paper, we propose a GA (Genetic Algorithm) image restoration method which has PSF (Point Spread Function) parameters as genes. The proposed technique restores an original image from its observation image which has been blurred partially by defocusing of a lens system. Though the degraded model of an image is a Gaussian function type, the value of distribution of the parameter which is assumed to be space variant is exactly unknown at each place. For this case, the evaluation function based on 'Regularization Theory' was proposed and some simulation experiments were performed, so that the validity has been shown on this study.

Paper Details

Date Published: 5 March 1999
PDF: 8 pages
Proc. SPIE 3646, Nonlinear Image Processing X, (5 March 1999); doi: 10.1117/12.341079
Show Author Affiliations
Tomokazu Tamaoki, Tokyo Metropolitan Institute of Technology (Japan)
Noboru Funakubo, Tokyo Metropolitan Institute of Technology (Japan)

Published in SPIE Proceedings Vol. 3646:
Nonlinear Image Processing X
Edward R. Dougherty; Jaakko T. Astola, Editor(s)

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