DocumentCode
3194279
Title
The diffusion performance analysis of variational PDE based neural network restoration models
Author
Wu, Ya-Dong ; Sun, Yu ; Zhang, Hong-Ying
Author_Institution
Coll. of Comput. Sci. & Technol., Southwest Univ. of Sci. & Technol., Mianyang
fYear
2008
fDate
25-27 May 2008
Firstpage
834
Lastpage
837
Abstract
In this paper, we introduce two variational PDEs (Partial Differential Equations) as the regularization terms to the image restoration model based on the modified Hopfield neural network. The performance of these regularization terms is analyzed from the viewpoint of nonlinear diffusion. It can be shown that the two proposed restoration models have superior edge preserving performance than the traditional restoration model.
Keywords
Hopfield neural nets; image restoration; partial differential equations; Hopfield neural network; diffusion performance analysis; image restoration model; neural network restoration models; partial differential equations; variational PDE; Atmospheric modeling; Computer science; Degradation; Educational institutions; Hopfield neural networks; Image restoration; Laplace equations; Neural networks; Partial differential equations; Performance analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Communications, Circuits and Systems, 2008. ICCCAS 2008. International Conference on
Conference_Location
Fujian
Print_ISBN
978-1-4244-2063-6
Electronic_ISBN
978-1-4244-2064-3
Type
conf
DOI
10.1109/ICCCAS.2008.4657899
Filename
4657899
Link To Document