Modified PCNN Model and Its Application to Mixed-Noise Removal

Pulse coupled neural networks (PCNN) model is a bionic system. It emulates the behavior of visual cortical neurons of cats and has been extensively applied in image processing. We proposed an adaptive mixed-noise removal algorithm, in this paper, based on making further improvements to L&A-PCNN, and combined with theoretical analysis and experimental analysis to obtain the self-adaptive definition of the key parameters of the improved model. The simulation results show that the improved algorithm is not only better than L&A-PCNN method in the theoretical results, but also realized the automation of mixed-noise removal.