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Adaptive weighted mean filtering algorithm based on city block distance
CAO Meng ZHANG Youhui WANG Zhiwei DONG Rui ZHEN Yingjuan
Journal of Computer Applications
2013, 33 (11):
3197-3200.
Concerning the defect that the traditional filtering window cannot be adaptively extended and the standard mean filter algorithm could blur edges easily, a new adaptive weighted mean filtering algorithm based on city block distance was proposed. First, the noise points can be detected with switch filtering ideas. Then, for each noise point, the window was extended according to the city block distance, and the window size was adaptively adjusted based on the number of signal points within the window. Last, the weighted mean of the signal points in the window was taken as the gray value of the noise points to achieve the effective recovery of the noise points. The experimental results show that the algorithm can effectively filter out salt-and-pepper noise, especially for the larger-noise-density image, and denoising effect is more significant.
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