Adaptive removal of salt-pepper noises through fast noise ratio estimation
Tao Zhu · Guangdian gongcheng · 2005
An adaptive salt-pepper removal algorithm is proposed, which can estimate noise ratio and change the filtering window automatically. In non-ideal image with salt-pepper noises, some regions are chosen at random from which every pixel is filtered by median filter through different filtering windows. Numbers of noise pixels for every region are obtained by comparing the filtered regions before filtering. These numbers are ranked and the median three numbers are taken to be weighted to get a ratio for every kind of window, thus three ratios are got and they are weighted to sum up to achieve the noise ratio. Then through T-S fuzzy model, choose the filtering model and the max filtering window and exclude noise pixels by way of thresholding in the filtering window. The rest pixels are summed up with adaptive weight according to the distance from centered pixel to get the estimation of the center pixel. Experiments prove that the proposed algorithm has higher accuracy with NMSE 20% smaller and is one time faster than classical median filter and center weighted median filters etc.