A new denoising method combines median filter with adaptive weighted median filter
Haixia Xiao, Jianguo Liu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2013
Natural images often suffer from the problem of noise. In this paper, we present a new denoising method which combines the adaptive weighted median filter with traditional median filter. Inspired by the image segmentation algorithm based on transition region, an image matrix based on the synthesized of local entropy and local variance is calculated. The values of matrix reflect the frequency and intensity of the gray level changes in the neighborhood windows. On the basis of the values of the matrix, the filtering strategy is that the traditional median filter acts in non-transition region, the adaptive weighted median filter acts in transition region, and the weights are set by the values of the matrix too. The major novelty of the proposed algorithm is that it can adequately utilize the advantages of the two filter methods above. Experimental results show that the proposed method outperforms the conventional methods in removing noise effectively and preserving image edges and details thus is suited for natural images denoising.