Title: Image restoration using Modified Recurrent Hopfield Neural Network

Authors: S. Uma, S. Annadurai

Addresses: Department of Electronics and Communication Engineering, Coimbatore Institute of Technology, Coimbatore 641 014, India. ' Government College of Technology, Coimbatore 641 013, India

Abstract: An approach to restore an image degraded by a blur function and corrupted by random noise is proposed using a Modified Recurrent Hopfield neural network (MRHNN) model. The existing Hopfield network takes more iteration to converge and results in poor quality images as the noise level increases. In the proposed network a fraction of the output of a neuron is fed only to higher order neurons resulting in reduced number of iterations as well as a better SNR. Two updating algorithms: the sequential update; n-simultaneous update are used with the proposed network.

Keywords: image restoration; modified HNN; Hopfield neural networks; energy function; random noise; MHNN; blur function; random noise; image degradation; image corruption.

DOI: 10.1504/IJSISE.2008.026798

International Journal of Signal and Imaging Systems Engineering, 2008 Vol.1 No.3/4, pp.264 - 272

Published online: 26 Jun 2009 *

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