A new detector for switching median filter

In this paper, a new detector for switching median filter is presented. The originality of this approach is that no a priori threshold is to be given. Instead, it is automatically computed from image pixels and based on the weighted mean and the weighted variance in a selected sliding window. The weights are inversely proportional to the grey levels difference between each pixel of the considered window and the mean value of this window. Results show that this new algorithm provides better performances in terms of PSNR and MAE than many other variants of switching median filter. It suppresses noise and preserves details. In addition, psycho visual results are of high quality.