A new rank-ordered method for removing random-valued impulse noise

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/).

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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  -