A New Adaptive Median Filter Based on Possibilistic Linear Models for Image Restoration

A novel partition center weighted median-type (PCWM) filter is proposed for improving the performance of median-based filters. The proposed filter achieves its effect through the linear combinations of the weighted output of the median filter and the related weighted input signal, and the weights are set based on possibilistic linear models concerning the states of the input signal sequence. The extensive experimental results included in this paper have demonstrated that the proposed filter is superior to a number of well-accepted median-based filters in the literature.