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http://dx.doi.org/10.6109/jkiice.2022.26.11.1637

Salt and Pepper Noise Removal Algorithm based on Euclidean Distance Weight  

Chung, Young-Su (Department of Intelligent Robot Engineering, Pukyong National University)
Kim, Nam-Ho (School of Electrical Engineering, Pukyong National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.26, no.11, 2022 , pp. 1637-1643 More about this Journal
Abstract
In recent years, the demand for image-processing technology in digital marketing has increased due to the expansion and diversification of the digital market, such as video, security, and machine intelligence. Noise-processing is essential for image-correction and reconstruction, especially in the case of sensitive noises, such as in CT, MRI, X-ray, and scanners. The two main salt and pepper noises have been actively studied, but the details and edges are still unsatisfactory and tend to blur when there is a lot of noise. Therefore, this paper proposes an algorithm that applies a weight-based Euclidean distance equation to the partial mask and uses only the non-noisy pixels that are the most similar to the original as effective pixels. The proposed algorithm determines the type of filter based on the state of the internal pixels of the designed partial mask and the degree of mask deterioration, which results in superior noise cancellation even in highly damaged environments.
Keywords
Salt and Pepper noise; Partial mask; Euclidean distance; Weight factor; PSNR;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 R. Gandikota and M. S. M, "Pixel Noise Localization Algorithm for Indian Satellite Data Quality Control: A Novel Approach," in Proceedings of 2019 8th Mediterranean Conference on Embedded Computing, Kuala Lumpur, Malaysia, pp. 7759-7762, 2022.
2 A. M Menon, E. Eldho, G. M Benny, and D. Sudarsan, "A Novel Approach for Noise Removal from Hand Written Manuscript using Enhanced Gibbs Sampling Algorithm," in Proceedings of 2019 International Conference on Wireless Communications Signal Processing and Networking, Chennai, India, pp. 497-500, 2019.
3 A. Bandyopadhyay, K. Deb, A. Das, and R. Bag, "Manhattan Distance based Nearest Vicinity Guided Filter Design for High Density Salt and Pepper Noise Removal," in Proceedings of 2020 IEEE 1st International Conference for Convergence in Engineering, Kolkata, India, pp. 184-188, 2020.
4 P. Zhang and F. Li, "A New Adaptive Weighted Mean Filter for Removing Salt-and-Pepper Noise," IEEE Signal Processing Letters, vol. 21, no. 10, pp. 1280-1283, Jun. 2014.   DOI
5 B. W. Cheon and N. H. Kim, "A Filter Algorithm based on Partial Mask and Lagrange Interpolation for Impulse Noise Removal," Journal of the Korea Institute of Information and Communication Engineering, vol. 26, no. 5, pp. 675-681, May 2022.   DOI
6 J. Shedbalkar, K. Prabhushetty, and A. Inchalc, "A Comparative Analysis of Filters for Noise Reduction and Smoothening of Brain MRI Images," in Proceedings of 2021 6th International Conference for Convergence in Technology, Maharashtra, India, pp. 1-6, 2021.
7 K. S. Srinivasan and D. Ebenezer, "A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises," IEEE Signal Processing Letters, vol. 14, no. 3, pp. 189-192, Feb. 2007.   DOI
8 C. H. Hsieh, P. C. Huang, and Q. Zhao, "Impulse Noise Replacement with Adaptive Neighborhood Median Filtering," in Proceedings of 2018 International Conference on Machine Learning and Cybernetics, Chengdu, China, pp. 491-496, 2018.
9 S. Esakkirajan and T. Veerakumar, "Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter," IEEE Signal Processing Letters, vol. 18, no. 5, pp. 287-290, Mar. 2011.   DOI
10 H. Y. Lee and N. H. Kim, "Salt and Pepper Noise Removal using Effective Pixels and Linear Interpolation," Journal of the Korea Institute of Information and Communication Engineering, vol. 26, no. 7, pp. 989-995, Jul. 2022.   DOI