Title :
Cellular neural network based weighted median filter for real time image processing
Author :
Kowalski, Jacek ; Kacprzak, Tomasz
Author_Institution :
Inst. of Electron., Tech. Univ. Lodz, Poland
fDate :
6/23/1905 12:00:00 AM
Abstract :
This paper describes a VLSI implementation of an analog image weighted median filter based on a cellular neural network (CNN) architecture for real-time applications. This filter consists of feedforward nonlinear template B operating within the window of 3 by 3 pixels around the central pixel being filtered. The basic block of this filter is a nonlinear coupler circuit, which realizes a nonlinear template B of the CNN. A technology for implementation is CMOS AMS 0.8 μm CYE
Keywords :
CMOS integrated circuits; VLSI; analogue processing circuits; cellular neural nets; coupled circuits; feedforward neural nets; image processing; median filters; nonlinear network synthesis; real-time systems; 0.8 micron; CMOS AMS CYE technology; VLSI implementation; analog image weighted median filter; cellular neural network architecture; feedforward nonlinear template; nonlinear coupler circuit; nonlinear template; pixels; real time image processing; real-time applications; Brightness; Cellular neural networks; Circuits; Digital filters; Equations; Image processing; Information filtering; Information filters; Nonlinear filters; Steady-state;
Conference_Titel :
Image Processing, 2001. Proceedings. 2001 International Conference on
Conference_Location :
Thessaloniki
Print_ISBN :
0-7803-6725-1
DOI :
10.1109/ICIP.2001.959074
