DocumentCode :
771022
Title :
Variational PDE based image restoration using neural network
Author :
Wu, Y.-D. ; Sun, Y. ; Zhang, H.-Y. ; Sun, S.-X.
Author_Institution :
Coll. of Comput. Sci. & Technol., Southwest Univ. of Sci. & Technol., Mianyang
Volume :
1
Issue :
1
fYear :
2007
fDate :
3/1/2007 12:00:00 AM
Firstpage :
85
Lastpage :
93
Abstract :
Two variational partial differential equations as regularisation terms are proposed for the image restoration model based on the modified Hopfield neural network. One is based on a harmonic model and the other is based on a total variation model. The performance of these regularisation terms is analysed from the viewpoint of nonlinear diffusion. It can be shown that the two proposed restoration models have edge-preserving performance superior to that of the traditional restoration model. Two algorithms have been proposed on the basis of the harmonic restoration model and the total variation model. Experimental results show that the proposed algorithms are more effective than the traditional algorithm
Keywords :
Hopfield neural nets; image restoration; partial differential equations; variational techniques; edge-preserving performance; harmonic restoration model; image restoration; modified Hopfield neural network; nonlinear diffusion; regularisation terms; total variation model; variational PDE; variational partial differential equations;
fLanguage :
English
Journal_Title :
Image Processing, IET
Publisher :
iet
ISSN :
1751-9659
Type :
jour
DOI :
10.1049/iet-ipr:20050383
Filename :
4149699
Link To Document :
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