DocumentCode
2733638
Title
Image restoration using Lagrange programming neural networks
Author
Zhu, Xinen ; Zhang, Shaoting ; Constantinides, A.G.
Author_Institution
Dept. of Electr. Eng., Imperial Coll., London
fYear
1991
fDate
8-14 Jul 1991
Abstract
Summary form only given, as follows. An approach involving the use of Lagrange programming neural networks to restore degraded images is proposed. Three kinds of neurons take part in the restoration process: parameter neurons, variable neurons, and Lagrange neurons. The parameter neurons adapt to various input parameters, while the variable and Lagrange neurons construct a canonical computational circuit to fulfill fundamental solution-finding computation. Maximum entropy restoration is completed with ease by taking advantage of the features of robust stability and functional flexibility of the neural network. High-quality images were obtained in experiments
Keywords
computerised picture processing; neural nets; Lagrange neurons; Lagrange programming neural networks; degraded images; functional flexibility; image restoration; input parameters; maximum entropy restoration; parameter neurons; robust stability; solution-finding computation; variable neurons; Circuits; Degradation; Educational institutions; Entropy; Image restoration; Lagrangian functions; Neural networks; Neurons; Robust stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location
Seattle, WA
Print_ISBN
0-7803-0164-1
Type
conf
DOI
10.1109/IJCNN.1991.155516
Filename
155516
Link To Document