High-density salt-and-pepper noise removal using adaptive weighted kriging interpolation filter

An adaptive weighted kriging interpolation filter for removal of high-density salt-and-pepper noise (SPN) in images is proposed. The proposed scheme introduces a method for computing the estimation value of a noisy pixel in the center of the processing window. Different from the existing adaptive decision based on kriging interpolation algorithm, the proposed kriging interpolation for different adaptive windows cares about the action of not only the Euclidean distance between nonnoisy pixels but also the size of the current processing window. Therefore, the corrupted pixel is replaced by the inverse filtering-radius weighted sum of kriging interpolations for different adaptive windows. The final processing window is required to include at least three noncorrupted pixels. The proposed algorithm is extensively evaluated on a variety of benchmark images and the experimental results show that it outperforms several standard and popular algorithms in terms of visual quality and quantitative results.