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Proceedings Paper

On The Application Of Neural Networks To The Solution Of Image Restoration Problems
Author(s): J. B. Abbiss; B. J. Brames; M. A. Fiddy
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Paper Abstract

The purpose of this paper is to describe the implementation of a super-resolution (or spectral extrapolation) procedure on a neural network, based on the Hopfield model. This was first proposed by Abbess et al.1 We show the computational advantages and disadvantages of such an approach for different coding schemes and for networks consisting of very simple two state elements as well as those made up of more complex nodes capable of representing a continuum. With the appropriate hardware, we show that there is a computational advantage in using the Hopfield architecture over some alternative methods for computing the same solution. We also discuss the relationship between a particular mode of operation of the neural network and the regularized Gerchberg-Papoulis algorithm.

Paper Details

Date Published: 17 May 1989
PDF: 9 pages
Proc. SPIE 1058, High Speed Computing II, (17 May 1989); doi: 10.1117/12.951676
Show Author Affiliations
J. B. Abbiss, Spectron Development Laboratories, Inc (United States)
B. J. Brames, Spectron Development Laboratories, Inc (United States)
M. A. Fiddy, University of Lowell (United States)

Published in SPIE Proceedings Vol. 1058:
High Speed Computing II
Keith Bromley, Editor(s)

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