A New Kind of Hybrid Filter Based on the Peak-and-Valley Filter and PCNN

Pulse coupled neural network (PCNN) has gained widely research as a new artificial neural network. It derives directly from the studies of the small mammal´s visual cortex. The peak-and-valley filter can keep the details of image sufficiently if the density of noise is low enough. But for the image that is badly contaminated with noise, the effect of the peak-and-valley filter is inadequate. To overcome this shortage, this paper suggests a kind of designing project of the hybrid filter that applies the ideas of the PCNN and the peak-and-valley filter. PCNN is a model with multiple parameters and finding the proper values of these parameters is an onerous task. So a simplified PCNN is put forward and its performance in removing Salt-and-pepper noise of image is discussed in this article. The theory analysis and the simulation experiments of the image processing indicate that this kind of filter can not only remove noise effectively but also keep the details of the image sufficiently.