An Improved Denoising Method Based on Stationary Wavelet Transform

DOI

10.2991/cecs-18.2018.82How to use a DOI?

Keywords

wavelet denoising, stationary wavelet transformation, threshold function, signal to noise ratio.

Abstract

It is quite difficult to analyze experimental signals since they have low Signal-to-Noise Ratio (SNR). Discrete Stationary Wavelet Transform (SWT) can be used for signal denoising because of its energy concentration and shift invariance feature. this paper focuses on the noise reduction algorithms based on SWT and proposed a new threshold function for better denoising effect. The method is experimentally evaluated and simulated. The result shows that the proposed method is an effective tool for signal denoising.

Copyright

© 2018, 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  - Xiaoli Wang
AU  - Yongfeng Dai
PY  - 2018/07
DA  - 2018/07
TI  - An Improved Denoising Method Based on Stationary Wavelet Transform
BT  - Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
PB  - Atlantis Press
SP  - 481
EP  - 485
SN  - 2352-538X
UR  - https://doi.org/10.2991/cecs-18.2018.82
DO  - 10.2991/cecs-18.2018.82
ID  - Wang2018/07
ER  -