Design of high speed weighted fuzzy mean filters with generic LR fuzzy cells

A hardware design method for a high-speed weighted fuzzy mean (WFM) filter is proposed in this paper. The WFM filter is powerful for removing heavy additive impulse noises from images. When the probability of occurrence of mixed impulse noises is over 0.3, the WFM filter can recover the noise-corrupted image quite well in contrast with several conventional filters. For the dedicated hardware implementation, the WFM filter is synthesized with the generic LR fuzzy cells which realize high speed fuzzy inference. The hardware complexity corresponds to the amount of input samples which is also much simpler than the conventional median filter. The simulation and chip layout exhibit that up to 90 256/spl times/256 images can be filtered per second by the very small-sized WFM filter.