Median-based filters with prediction error processing for video restoration

This paper deals with denoising of color video sequences using median-based filters. It is proved that application of prediction error processing results in improved efficiency of video restoration. The basic idea is to predict a pixel value by using a nonlinear filter, and then to compare this value to that in the input (corrupted) image. Usually these two values are different and a decision has to be made about the pixel value at the filler output. This value can be considered as a sum of the prediction and the prediction error processed in some way. For example, large values of prediction errors are set to zero because they are can be classified as caused by impulsive noise samples. Soft decisions on classification of prediction errors lead to good results for test images