GA image restoration using parameters of degrading and restoring functions as genes

Tomokazu Tamaoki; Noboru Funakubo

doi:10.1117/12.341079

5 March 1999 GA image restoration using parameters of degrading and restoring functions as genes

Tomokazu Tamaoki, Noboru Funakubo

Proceedings Volume 3646, Nonlinear Image Processing X; (1999) https://doi.org/10.1117/12.341079
Event: Electronic Imaging '99, 1999, San Jose, CA, United States

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.

Citation Download Citation

Tomokazu Tamaoki and Noboru Funakubo "GA image restoration using parameters of degrading and restoring functions as genes", Proc. SPIE 3646, Nonlinear Image Processing X, (5 March 1999); https://doi.org/10.1117/12.341079

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