Abstract:

In this paper, a new filter algorithm was proposed for pepperandsalt noise suppression. Firstly, the neighborhood of each given pixel is partitioned by Kmeans clustering according to the local grey level distribution. Secondly, the recognition rules for noisepolluted pixel detection are constructed, and the noise pixel can be detected based on multilayer binary tree decision. The proposed algorithm only filters the recognized noise pixels without changing those nonpolluted pixel values. Experimental results show that the proposed algorithm can efficiently preserve informative details when filtering image noise. For those images with strong noise pollution, the proposed algorithm outperforms both median filter and the algorithm proposed in［7］.

Key words: pepper-and-salt noise;K-means clustering;binary tree;image filtering;noise detection