2-3 September 2021
Publication Links
IJACSA
Special Issues
Article Details
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Iterative Removing Salt and Pepper Noise based on Neighbourhood Information
Digital Object Identifier (DOI) : 10.14569/IJACSA.2018.090136
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 9 Issue 1, 2018.
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.
Keywords: Salt and pepper noise; noise detection; neighbourhood similarity; detail preserving denoising
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}
}
