Title :
Adaptive image restoration using Hopfield neural network
Author :
Ghennam, Souheila ; Benmahammed, Khier
Author_Institution :
Dept. of Electron., Ferhat Abbas Univ., Setif, Algeria
Abstract :
In this paper, a solution to the restoration problem of degraded and noisy image is proposed, using the modified Hopfield network. To improve the network performances, the eliminating highest error EHE is used. In order to keep the image structures unaltered, an adaptive regularization scheme is employed that allows better compromise between inversion degradation process and smoothing. To do this, the statistics analysis is used to assign each pixel one regularization parameter according to its spatial activity
Keywords :
Hopfield neural nets; image restoration; Hopfield neural network; adaptive image restoration; adaptive regularization scheme; degraded image; image structures; noisy image; spatial activity; Additive noise; Artificial neural networks; Biological neural networks; Degradation; Gaussian noise; Hopfield neural networks; Image restoration; Neurons; Smoothing methods; Statistical analysis;
Conference_Titel :
Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal Processing Society Workshop
Conference_Location :
North Falmouth, MA
Print_ISBN :
0-7803-7196-8
DOI :
10.1109/NNSP.2001.943161