A new rank-ordered method for removing random-valued impulse noise
Authors
Hao Yang, Leiting Chen
Corresponding Author
Hao Yang
Available Online January 2016.
- DOI
- 10.2991/ifmeita-16.2016.141How to use a DOI?
- Keywords
- Random-valued impulse noise, Sub-neighborhood mean, Rank-ordered extension differences, Edge-preserving regularization.
- Abstract
In this paper, we present an effective statistic algorithm to remove the random-valued impulse noise. The proposed method takes full advantage of the sub-neighborhood mean of each pixel to reduce the missed and failed detection in high noise ratio. In the first phase, a statistic based on rank-ordered extension differences is defined to identify pixels which are noise candidates. In the second phase, all noisy pixels will be restored by an edge-preserving regularization filter. Simulation results show that the proposed method has better accuracy than many other existing techniques with high noise level.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Hao Yang AU - Leiting Chen PY - 2016/01 DA - 2016/01 TI - A new rank-ordered method for removing random-valued impulse noise BT - Proceedings of the 2016 International Forum on Management, Education and Information Technology Application PB - Atlantis Press SP - 771 EP - 774 SN - 2352-5398 UR - https://doi.org/10.2991/ifmeita-16.2016.141 DO - 10.2991/ifmeita-16.2016.141 ID - Yang2016/01 ER -