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Proceedings Paper

Blur detection using a neural network
Author(s): Chong Sze Tong
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Paper Abstract

Image restoration is an ill-posed inversion problem wherein an estimate of the ideal original image is to be extracted from a noisy and blurred observation. The ability to restore such a degraded digital image usually requires accurate knowledge of the blur function as well as additional information on the original image. Unfortunately, such a priori knowledge is not always accessible. This paper describes an iterative scheme for the identification of the blurring by making use of the neural network paradigm and the assumption of physical constraints on the blurring process.

Paper Details

Date Published: 7 June 1995
PDF: 11 pages
Proc. SPIE 2563, Advanced Signal Processing Algorithms, (7 June 1995); doi: 10.1117/12.211411
Show Author Affiliations
Chong Sze Tong, Hong Kong Baptist Univ. (Hong Kong)


Published in SPIE Proceedings Vol. 2563:
Advanced Signal Processing Algorithms
Franklin T. Luk, Editor(s)

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