Weighted order statistic image filter chip based on cellular neural network architecture

This paper describes a VLSI chip of an analog image weighted order statistic (WOS) filter based on cellular neural network (CNN) architecture for real-time applications. The chip has been implemented in CMOS AMS 0.8 μm CYE technology. This filter consists of feedforward nonlinear template B operating within the window of 3 by 3 pixels around the central pixel being filtered. The feedforward nonlinear CNN coefficients have been realized using programmable nonlinear coupler circuits. The WOS filter chip allows for processing of images with 300 pixels horizontal resolution. Functional tests of the chip have been performed using a special test set-up for PAL composite video signal processing. Using the set-up real images have been filtered by WOS filter chip under test.