Iterative Removing Salt and Pepper Noise based on Neighbourhood Information

Abstract

Denoising images is a classical problem in low-level computer vision. In this paper, we propose an algorithm which can remove iteratively salt and pepper noise based on neighbourhood while preserving details. First, we compute the probability of different window without free noise pixel by noise ratio, and then determine the size of window. After that the corrupted pixel is replaced by the weighted eight neighbourhood pixels. If the neighbourhood information does not satisfy the de-noising condition, the corrupted pixels will recover in the subsequent iterations.

Authors and Affiliations

Liu Chun, Sun Bishen, Tan Kun, Ma Yingrui

Keywords

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  • EP ID EP261569
  • DOI 10.14569/IJACSA.2018.090136
  • Views 134
  • Downloads 0

How To Cite

Liu Chun, Sun Bishen, Tan Kun, Ma Yingrui (2018). Iterative Removing Salt and Pepper Noise based on Neighbourhood Information. International Journal of Advanced Computer Science & Applications, 9(1), 261-265. https://europub.co.uk/articles/-A-261569