Salt and pepper noise reduction and edge detection algorithm based on neutrosophic logic

• Autorzy: Arulpandy P. , Trinita Pricilla M.

Identyfikatory

DOI

doi.org/10.7494/csci.2020.21.2.3438

• Języki publikacji: EN

Abstrakty

EN

Noise reduction of images is a challenging task in image processing. Salt and pepper noise is one kind of noise that affects a gray-scale image significantly.Generally, the median filter is used to reduce salt and pepper noise; it gives optimum results while compared to other image filters. Median filter works only up to a certain level of noise intensity. Here we proposed a neighborhoodbased image filter called nbd-filter, it works perfectly for gray image regardless of noise intensity. It reduces salt and pepper noise significantly at any noise level and produces a noise-free image. Further, we proposed an edge detection algorithm based on the neutrosophic set, it detects edges efficiently for images corrupted by noise and noise-free images. Neutrosophic set (NS) is a powerful tool to deal with indeterminacy. Since most of the real-life images consists of indeterminate regions, Neutrosophy is a perfect tool for edge detection. In this paper, the neutrosophic set is applied to the image domain and a novel edge detection technique is proposed.

Słowa kluczowe

EN

neutrosophic set; digital image processing; image analysis; image denoising; edge detection

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2020
• Tom: T. 21 (2)
• Strony: 193--209
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Arulpandy P.

• Department of Mathematics, Bannari Amman Institute of Technology, Erode, Tamilnadu, India

autor

Trinita Pricilla M.

• Department of Mathematics, Nirmala College for Women, Coimbatore, Tamilnadu, India

Bibliografia

• [1] Arulpandy P., Pricilla M.T.: Reduction of indeterminacy of grayscale image in bipolar neutrosophic domain, Neutrosophic Sets and Systems, vol. 28(1), 2019. https://doi.org/10.5281/zenodo.3382501.
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• [3] Cheng H.D., Guo Y.: A new neutrosophic approach to image thresholding, New Mathematics and Natural Computation, vol. 4(3), pp. 291–308, 2008.
• [4] Cheng H.D., Guo Y., Zhang Y.: A novel image segmentation approach based on neutrosophic set and improved fuzzy C-means algorithm, New Mathematics and Neural Computation, vol. 7(1), pp. 155–171, 2011. https://doi.org/10.1142/S179 3005711001858.
• [5] Guo Y., Cheng H.D., Zhang Y.: A new neutrosophic approach to image denoising, New Mathematics and Neural Computation, vol. 5(3), pp. 653–662, 2009. https: //doi.org/10.1142/S1793005709001490.
• [6] Guo Y., S¸eng¨ur A.: A novel image edge detection algorithm based on neutrosophic set, Computers and Electrical Engineering, vol. 40(8), pp. 3–25, 2014. https://doi.org/10.1016/j.compeleceng.2014.04.020.
• [7] Ma H., Nie Y.: A two-stage filter for removing salt-and-pepper noise using noise detector based on characteristic difference parameter and adaptive directional mean filter, PLOS ONE, vol. 13(10), 2018. https://doi.org/10.1371/journal.pone .0205736.
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• [14] Smarandache F.: A unifying field in logics: neutrosophic logic. Neutrosophy, neutrosophic set, neutrosophic probability and statistics, 3rd edition, American Research Press, 2003.
• [15] Smarandache F.: Neutrosophic Set – A Generalization of the Intituitionistic Fuzzy Set, International Journal of Pure and Applied Mathematics, vol. 24(3), pp. 287–297, 2005.
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