ACS/IEEE International Conference on Computer Systems and Applications (AICCSA'01) Restoration Method Using a Neural Network Model Beirut, Lebanon June 25-June 29 ISBN: 0-7695-1165-1
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 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||