A self-adjusting weighted median filter for removing impulse noise in images
Chun‐Te Chen, Liang‐Gee Chen · 2002
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 data 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 mean square error (MSE) or mean absolute error (MAE) measurement than the standard median filter. At the same time, the quality of the filter output has been enhanced significantly. Finally, a demonstration chip of this weighted median filter for the 5/spl times/5 window size is also presented.