A New Design Method of General Weighted Median Filters Admitting Negative Weights for Enhancement of Images Degraded by Additive Noise

摘要

In this paper, we propose a new design method of general weighted median filters admitting negative weights for enhancement of images degraded by additive impulsive noise. The general weighted median (GWM) filters are already proposed as frequency selective nonlinear filters. Nevertheless, no one considers how to apply the GWM filters for enhancing degraded images. To enhance images degraded by additive noise, preferable frequency response is varied greatly with positions of window in images. Therefore, GWM filters with fixed weights are not preferable in image processing. Proposed method consists with three steps. At first, we divide block in sliding windows of filters into some number of classes according to difference of spectral characteristics. Second, we optimize some number of GWM filters to have proper frequency response in each class of block. At last, the GWM filters switched in each class are used for enhancement of images. To prepare the GWM filters in each class, the proposed filtering method is better than the GWM filters with fixed weights. Through some simulations, we show the above efficiency of the proposed filters comparing to the original WM filters and linear filters. The proposed method has the robustness for impulsive noise contamination and the frequency selective filtering property.