DocumentCode :
296165
Title :
Restoration of images degraded by space-variant distortion using a neural network
Author :
Perry, Stuart W. ; Guan, Ling
Author_Institution :
Dept. of Electr. Eng., Sydney Univ., NSW, Australia
Volume :
4
fYear :
1995
fDate :
Nov/Dec 1995
Firstpage :
2067
Abstract :
This paper introduces a neural network algorithm to the restoration of images suffering a known form of space-variant distortion. Using multiple weighting matrices to represent space-variance, the algorithm provides high quality restorations. The algorithm will also be shown to be very computationally inexpensive due to the ability to minimise the neural network´s energy in the most efficient manner
Keywords :
image restoration; minimisation; neural nets; computationally inexpensive algorithm; image restoration; multiple weighting matrices; neural network energy minimisation; space-variant distortion; Additive noise; Computer networks; Degradation; Equations; Image restoration; Neural networks; Neurons; Pixel; Quadratic programming; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
Type :
conf
DOI :
10.1109/ICNN.1995.488993
Filename :
488993
Link To Document :
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