27 October 2018 High-density salt-and-pepper noise removal using adaptive weighted kriging interpolation filter
Zhen Zhang, Xianwei Rong, Ming Li, Xiaoyan Yu
Author Affiliations +
Abstract
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.
© 2018 SPIE and IS&T 1017-9909/2018/$25.00 © 2018 SPIE and IS&T
Zhen Zhang, Xianwei Rong, Ming Li, and Xiaoyan Yu "High-density salt-and-pepper noise removal using adaptive weighted kriging interpolation filter," Journal of Electronic Imaging 27(5), 053045 (27 October 2018). https://doi.org/10.1117/1.JEI.27.5.053045
Received: 30 June 2018; Accepted: 26 September 2018; Published: 27 October 2018
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Digital filtering

Image processing

Bridges

Image filtering

Visualization

Image segmentation

Nonlinear filtering

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