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Restoration Method Using a Neural Network Model
Beirut, Lebanon June 25-June 29
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AICCSA.2001.933963ACS/IEEE International Conference on ...
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Nadia Zenati, Development center of advanced technologies
Karim Achour, Development center of advanced technologies
Abstract: In this paper, we consider the problem of image restoration degraded by a shift invariant blur function and corrupted by white Gaussian noise. We propose a modified Hopfield neural network based image restoration. Two algorithms with two updating modes using the modified Hopfield neural network are presented: 1) the sequential updates, and 2) the n-simultaneous updates. In the sequential algorithm, only one element of the state is updated at time (t+1) while the rest are left unchanged, otherwise, in the n-simultaneous algorithm all elements of the state are updated simultaneously. Lastly, we present some image restoration results which attest the efficiency of our method.
Citation:
Nadia Zenati, Karim Achour, "Restoration Method Using a Neural Network Model," aiccsa, pp.0122, ACS/IEEE International Conference on Computer Systems and Applications (AICCSA'01), 2001
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