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A neural network for deblurring an image

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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