Abstract
This paper proposes a novel iterative algorithm for removal of salt-and-pepper impulse noises. Even if the noise level is as high as 90 %, this proposed methodology ensures elimination of all the impulse noises while restoring the fine details of gray-scale images. Most of the salt-and-pepper noise removal techniques try to search for impulse noise from the images, but this proposed algorithm searches for the non-noisy points and removes the impulse points found in vicinity. The algorithm does the process iteratively but with low time complexity compared to most of the modern powerful algorithms. This simple straight forward algorithm produces the denoising image that gives better peak signal-to-noise ratio (PSNR) than other existing algorithms.
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Halder, A., Halder, S., Chakraborty, S. (2016). A Novel Iterative Salt-and-Pepper Noise Removal Algorithm. In: Das, S., Pal, T., Kar, S., Satapathy, S., Mandal, J. (eds) Proceedings of the 4th International Conference on Frontiers in Intelligent Computing: Theory and Applications (FICTA) 2015. Advances in Intelligent Systems and Computing, vol 404. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2695-6_54
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DOI: https://doi.org/10.1007/978-81-322-2695-6_54
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