DocumentCode :
2286142
Title :
Boolean design of binary initialized and coupled CNN image processing operators
Author :
Monnin, D. ; Koneke, A. ; Hérault, J.
Author_Institution :
ISL, Saint-Louis, France
fYear :
2002
fDate :
22-24 Jul 2002
Firstpage :
124
Lastpage :
131
Abstract :
As soon as an image processing operator can be expressed as a linearly separable Boolean function involving a cell and its neighborhood, there is a way of straightforwardly deriving an equivalent cellular neural network (CNN) operation. An appropriate method had already been introduced for the robust design of uniformly initialized uncoupled CNN operators, and is now applied to the design of binary initialized and coupled CNN operators. A way of implementing in a unique operator two different Boolean functions conditioning the white-to-black and the black-to-white transitions, respectively, is also presented.
Keywords :
Boolean functions; VLSI; cellular neural nets; image processing; Boolean design; Boolean functions; binary initialized coupled CNN image processing operators; black-to-white transitions; cellular neural network; linearly separable Boolean function; robust design; white-to-black transitions; Boolean functions; Cellular neural networks; Convolution; Design methodology; Image analysis; Image processing; Nonlinear filters; Output feedback; Robustness; State feedback;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cellular Neural Networks and Their Applications, 2002. (CNNA 2002). Proceedings of the 2002 7th IEEE International Workshop on
Print_ISBN :
981-238-121-X
Type :
conf
DOI :
10.1109/CNNA.2002.1035044
Filename :
1035044
Link To Document :
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