Cart (Loading....) | Create Account
Close category search window
 

A neural network for deblurring an image

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Jubien, C.M. ; Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada ; Jernigan, M.E.

A neural network architecture for deblurring a blurry scene without prior knowledge of the blur is proposed. Two different training algorithms are described, one a standard neural network training algorithm (employing the least mean squares (LMS) rule) and the second an original algorithm, dubbed algorithm-X. Both were successful for developing inverse blur filters to enhance a blurry picture. Algorithm-X is computationally less complex than the LMS algorithm, and in tests comparing the training times of the two algorithms, algorithm-X was found to be faster

Published in:

Communications, Computers and Signal Processing, 1991., IEEE Pacific Rim Conference on

Date of Conference:

9-10 May 1991

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.