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arXiv · 1708.05019

Salt-n-pepper noise filtering using Cellular Automata

Dimitrios Tourtounis·Nikolaos Mitianoudis·Georgios Ch. Sirakoulis
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Abstract

Cellular Automata (CA) have been considered one of the most pronounced parallel computational tools in the recent era of nature and bio-inspired computing. Taking advantage of their local connectivity, the simplicity of their design and their inherent parallelism, CA can be effectively applied to many image processing tasks. In this paper, a CA approach for efficient salt-n-pepper noise filtering in grayscale images is presented. Using a 2D Moore neighborhood, the classified "noisy" cells are corrected by averaging the non-noisy neighboring cells. While keeping the computational burden really low, the proposed approach succeeds in removing high-noise levels from various images and yields promising qualitative and quantitative results, compared to state-of-the-art techniques.

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Dimitrios Tourtounis, Nikolaos Mitianoudis, Georgios Ch. Sirakoulis. 2017-08-16. Salt-n-pepper noise filtering using Cellular Automata. https://arxiv.org/abs/1708.05019

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