Partition center weighted median filter for image denoising

Median filter is well known for removing impulsive noises but this filter distorts the fine structure of signals as well. In this paper, a novel median-type filter controlled by possibilistic linear models is proposed to preserve image details while effectively suppressing impulsive noises. The proposed filter achieves its effect through a summation of the input signal and the output of median filter, and the weights are set based on possibilistic linear models concerning the states of the input signal sequence. Some results of image denoising show the high performance of this filter. Moreover, the new filter also provides excellent robustness with respect to various percentages of impulse noise in our testing examples.