A self-adjusting weighted median filter for removing impulse noise in images

In this paper, an intelligent self-adjusting weighted median filter for removing impulsive noise in images is presented. Three main techniques are developed to implement this self-adjusting weighted median filter : an intelligent classification to divide the image da ta into the ”corrupted” pixels and the ”uncorrupted” pixels, an efficient algorithm to find the median output of any weight set, and a realistic training procedure without the noise free image to obtain the proper weights. Our simulations on some test images demonstrate that the proposed filter has less smoothing effect and smaller MAE or MSE measurement than the standard median filter. At the same time, the quality of filter output has enhanced significantly. Finally, a demonstration chip of this weighted median filter for the 5 X 5 window size is also presented in this paper.