Abstract
This paper proposes a simple and efficient method for designing a class of circularly-symmetric spatial linear filters implemented on cellular neural networks. The design method relies on a so-called 1-D prototype filter, with desired characteristics and on a 1-D to 2-D spatial frequency transformation. Several design examples are given, for 2-D low-pass and band-pass filters (both of FIR and IIR type) with imposed cut-off or peak frequency and a specified selectivity. Finally, simulation results are provided, on a real grayscale biomedical image.
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