DocumentCode
3281295
Title
Image restoration using a multilayer perceptron with a multilevel sigmoidal function
Author
Sivakumar, K. ; Desai, U.B.
Author_Institution
Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA
Volume
6
fYear
1992
fDate
10-13 May 1992
Firstpage
2917
Abstract
The problem of restoring a blurred and noisy image having many gray levels, without any knowledge of the blurring function and the statistics of the additive noise is considered. A multilevel sigmoidal function is used as the node linearity. Restoration is achieved by exploiting the generalization capabilities of the multilayer perceptron network. To overcome the burden of training time a segmentation scheme is suggested. Simulation results are also provided
Keywords
feedforward neural nets; image reconstruction; image segmentation; additive noise; blurred image; blurring function; gray levels; image restoration; multilayer perceptron; multilevel sigmoidal function; node linearity; noisy image; segmentation scheme; Additive noise; Artificial neural networks; Hopfield neural networks; Image restoration; Image segmentation; Knowledge engineering; Multilayer perceptrons; Neurons; Statistics; Wiener filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1992. ISCAS '92. Proceedings., 1992 IEEE International Symposium on
Conference_Location
San Diego, CA
Print_ISBN
0-7803-0593-0
Type
conf
DOI
10.1109/ISCAS.1992.230640
Filename
230640
Link To Document