A class of circularly-symmetric CNN spatial linear filters
2006 ◽
Vol 19
(2)
◽
pp. 299-316
◽
Keyword(s):
Low Pass
◽
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.
2012 ◽
Vol 490-495
◽
pp. 2381-2385
Keyword(s):
2020 ◽
Vol 9
(4)
◽
pp. 687-691