Effective and adaptive algorithm for pepper-and-salt noise removal

According to the characteristic of pepper-and-salt noise, the authors first classify pixels in a polluted image into two classes: suspected noise and noise-free pixels. For a suspected noisy pixel, by counting the number of closed grey-level and noise-free pixels in a neighbourhood, one can correctly determine a noise or a noise-free pixel. Noise filtering does not process noise-free pixels. For the noisy pixels, an adaptive filtering algorithm with weighting mean based on Euler distance achieves excellent noise removal and good detail preservation. The algorithm can handle different noise levels, and the authors do not need to manually adjust the parameters and thresholds. The experimental results indicate that the authors' proposed method effectively filters pepper-and-salt noise. The authors note that when noise-free and noisy pixels with the same grey level appear in the polluted images, the noise-removal performance by the proposed method is much more excellent than those of the other existing methods.