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Wavelet Transform-Based Signal Denoising in Low-Field NMR

Authors :
CHANG Xiao
SU Guan-qun
NIE Sheng-dong
Source :
Chinese Journal of Magnetic Resonance, Vol 35, Iss 3, Pp 393-406 (2018)
Publication Year :
2018
Publisher :
Science Press, 2018.

Abstract

Low-field NMR often uses permanent magnet. The signals obtained contain high level of white Gaussian noises, and have low signal-to-noise ratio (SNR). In recent years, many denoising methods have been proposed for low-field NMR measurements. Most of these methods can remove noises without losing useful information contained in the original signals. Wavelet transform is the most popular denoising method among them. In this paper, we first introduced the theory of wavelet transform analysis, followed by review of three wavelet transform denoising methods for low-field NMR, namely the wavelet threshold method, the wavelet transform modulus maximum method and the correlation of wavelet coefficient method. Finally, we showed that four parameters could be calculated to evaluate the denoising performance.

Details

Language :
Chinese
ISSN :
10004556
Volume :
35
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Chinese Journal of Magnetic Resonance
Publication Type :
Academic Journal
Accession number :
edsdoj.39808b7f22b466da706e0496a0acc99
Document Type :
article
Full Text :
https://doi.org/10.11938/cjmr20182615#