2nd Order 2-D Spatial Filters and Cellular Neural Network Implementations

Abstract

In this paper 2-D discrete-space filters are generated from their analog counterparts and implemented by Cellular Neural Networks (CNN). To this end, first 2-D analog transfer functions are obtained from their 1-D counterparts. Then, the corresponding difference equations are obtained by discretization of 2-D analog filter differential equations, which are then implemented by CNN. Simulation results are presented.