DocumentCode
352152
Title
Image intensity conversion via cellular neural networks
Author
Nakaguchi, Toshiya ; Tanji, Yuichi ; Tanaka, Mamoru
Author_Institution
Dept. of Electr. & Electron. Eng., Sophia Univ., Tokyo, Japan
Volume
4
fYear
2000
fDate
2000
Firstpage
125
Abstract
The image intensity conversion via CNN is presented. The intensity conversion is defined as a nonlinear optimization problem, and the templates of CNN for solving it are optimally designed. Since human visual sensitivity and linear quantization of original image are used to design the templates, it gives a smooth image preserving edge information such as character parts
Keywords
Lyapunov methods; cellular neural nets; edge detection; image coding; quantisation (signal); CNN; cellular neural networks; character parts; edge information; human visual sensitivity; image intensity conversion; linear quantization; nonlinear optimization problem; smooth image; templates; Cellular neural networks; Design optimization; Feedforward systems; Hardware; Humans; Image converters; Neural networks; Piecewise linear techniques; Quantization; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
Conference_Location
Geneva
Print_ISBN
0-7803-5482-6
Type
conf
DOI
10.1109/ISCAS.2000.858704
Filename
858704
Link To Document