A new adaptive center weighted median filter using counter propagation networks

A new type of adaptive center weighted median filters is developed for impulsive noise reduction of an image without the degradation of an original signal. The weight in the proposed filter is decided by the weight controller based on counter propagation networks. This controller classifies an input vector into some cluster according to its feature and gives the weight corresponding to the cluster. The parameters in the weight controller are adjustable by using the learning algorithm. The degradation of the original signal can be reduced by the proposed technique. An example is also given to illustrate the utility of the proposed technique.