Image Restoration Using Neural Networks

Authors:
Souheila Ghennam;Khier Benmahammed
Affiliations:
-;-
Venue:
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Year:
2001

Citing 3
Cited 1

Digital Image Processing

Digital Image Processing
Hopfield neural network based algorithms for image restoration andreconstruction. II. Performance analysis

IEEE Transactions on Signal Processing
General choice of the regularization functional in regularized image restoration

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Multiresolution Support for Adaptive Image Restoration Using Neural Networks

ICANN '02 Proceedings of the International Conference on Artificial Neural Networks

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Abstract

For resolving a restoration problem of degraded and noisy image, we investigate the Hopfield neural network, and we employ the eliminating highest error EHE criterion in intention to improving performances of network. Moreover, with the purpose to make a better restoration, we take in consideration a human perception in restoration process. To do this, we introduce an adaptive regularization scheme, with contribution of a local statistical analysis, to assigning each pixel one regularization parameter regarding to its spatial activity. Due to various values of regularization parameter, this scheme permit us expanding the one network to a network of network NON, which we subsequently elucidate its analogy with the human visual system, a cortex.