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.

Liu Chun, Sun Bishen, Liu Shaohui, Tan Kun and Ma Yingrui, “Iterative Removing Salt and Pepper Noise based on Neighbourhood Information” International Journal of Advanced Computer Science and Applications(IJACSA), 9(1), 2018. http://dx.doi.org/10.14569/IJACSA.2018.090136

@article{Chun2018,
title = {Iterative Removing Salt and Pepper Noise based on Neighbourhood Information},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090136},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090136},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {1},
author = {Liu Chun and Sun Bishen and Liu Shaohui and Tan Kun and Ma Yingrui}
}