Adaptive Sequentially Weighted Median Filter for Image Highly Corrupted by Impulse Noise

To tackle the difficulties in the detection and removal of impulse noise faced by the existing filters, and to further improve the denoising performance, we propose an adaptive sequentially weighted median filter for image corrupted by impulse noise. In the proposed method, a noise detector employing the $3\sigma $ principle of normal distribution and the local intensity statistics, is proposed; and a sequentially weighted median filter with a neighborhood of adaptive size, is proposed for noise removal, in which the weighted operator is derived in reference to the spatial distances from central noisy pixel, i.e., the weighting coefficients are sequentially inversely proportional to the spatial distances. The experimental results confirm that the proposed method outperforms the existing filters, excelling in the capability of noise removal, structure and edge information preservation.