Non-linear filtration of impulse noise by means of cellular neural networks

The synthesis of nonlinear impulse noise filters in the form of feedforward cellular neural network and two-layer perseptron network are considered. Neural filters are used for cancelling the “salt and pepper”-type interference from half-tone images. It is shown that the filter in the form of cellular neural network surpasses two-layer perseptron filter in the filtration accuracy. Neural filters ensure a higher level of impulse noise suppression as compared with median filters.