| 光谱学与光谱分析 |
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| Analysis of Several Methods for Wavelet Denoising Used in Near Infrared Spectrum Pretreatment |
| HAO Yong，CHEN Bin*,ZHU Rui |
| College of Biological and Environment Engineering，Jiangsu University，Zhenjiang 212013, China |
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Abstract Based on the wavelet analysis, the noise of the near infrared first derivative spectrum of rapeseed oil is eliminated. Several popular wavelet denoising methods are introduced, including wavelet decomposition and reconstruction method, nonlinear wavelet soft-threshold denoising method, and wavelet transform modulus maxima method，The results show that the wavelet transform modulus maxima method is the best, the nonlinear wavelet soft-threshold method is the second, and other are worse. The wavelet transform modulus maxima method can produce more precise model with little deviation.
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Received: 2005-06-22
Accepted: 2005-11-08
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Corresponding Authors:
CHEN Bin
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| Cite this article: |
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HAO Yong,CHEN Bin,ZHU Rui. Analysis of Several Methods for Wavelet Denoising Used in Near Infrared Spectrum Pretreatment[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2006, 26(10): 1838-1841.
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| URL: |
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https://www.gpxygpfx.com/EN/Y2006/V26/I10/1838 |
[1] Lü Rui-lan, WU Tie-jun, YU ling(吕瑞兰，吴铁军，于 玲). Spectroscopy and Spectral Analysis(光谱学与光谱分析)，2004，24(7): 826.
[2] HU Chang-hua, ZHANG Jun-bo, XIA Jun, et al(胡昌华，张军波，夏 军, 等). System Analysis and Design Based on MATLAB:Wavelet Transform(基于MATLAB的系统分析与设计：小波分析). Xi’an：Xi’an Electronic Science and Technology University Press(西安：西安电子科技大学出版社), 1999. 12.
[3] Stephane Mallat. A Wavelet Tour of Signal Processing(信号处理的小波导引). Beijing: China Machine Press(北京：机械工业出版社), 2002. 9.
[4] ZHENG Yong-mei, ZHANG Tie-qiang, ZHANG Jun, et al(郑咏梅，张铁强，张 军, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2004, 24(12): 1546
[5] Donoho D L. IEEE Transaction on Information Theory，1995，41(3): 613.
[6] Stephane Mallat，Wen Liang. IEEE Transaction on Information Theory, 1992, 38(2): 617.
[7] Kicey C J, Lennard C J. Fourier Analysis and Appl., 1997, 3(1): 63. |
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