| 光谱学与光谱分析 |
|
|
|
|
|
| Research of the Raman Signal De-Noising Method Based on Feature Extraction |
| FAN Xian-guang1, WANG Xiu-fen1, WANG Xin1*, XU Ying-jie1, QUE Jing1, WANG Xiao-dong1, HE Hao1, LI Wei1, ZUO Yong2 |
1. School of Aerospace Engineering, Xiamen University, Xiamen 361005, China
2. Changcheng Institute of Metrology & Measurement, The 1st Metrology &Measurement Research Centre of National Defense Science Industry of China, Beijing 100095, China |
|
|
|
|
Abstract To improve time resolution of the Raman measurement system, we need to adopt short scanning time. In this case, the weak Raman signal with vibrational spectrum of the molecular structure is easily to be buried by the high background noise, which influences the further analysis seriously. So it is necessary to de-noise the raw Raman signals. Conventional methods manage to de-noise signal by means of smoothing or averaging based on the difference between signal and noise in frequency characteristic or statistical features. They are commonly applied in the situation where the background noise is not so strong, and cannot give satisfactory results to the Raman signals with low signal-to-noise ratio. In this paper, the algorithm proposed detects peak positions and get peak half-width based on wavelet transform, and then reconstructs the Raman signals by least square fitting algorithm with characteristic parameters obtained, which extracts the useful signal from high background noise efficiently. In the simulation, the Raman curve fitted by the proposed algorithm was smooth, and the peak positions obtained were accurate, so the signal-to-noise ratio improved significantly. In the experiment, we adopted this algorithm to de-noise the tested Raman signal of Cefuroxime Axetil Tablets and Roxithromycin, respectively. The peak positions, peak half-width and amplitude were obtained and proved to be accurate. Therefore, the useful pure Raman signal could be recovered from the high background noise efficiently by the proposed algorithm, which improved the time resolution of Raman system. Both the simulation and the experiment showed that the proposed method could be easily performed with only a few parameters. Comparing with conventional methods, it could achieve satisfactory results under high background noise and provide accurate and reliable information for further analysis.
|
|
Received: 2015-08-31
Accepted: 2015-12-11
|
|
|
|
Corresponding Authors:
WANG Xin
E-mail: xinwang@xmu.edu.cn
|
|
[1] WEI Na, FENG Xu-qiao, ZHANG Xiao-fang, et al(韦 娜, 冯叙桥, 张孝芳，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2013, 33(3): 694.
[2] Keng H C, Hiro-o H，Shinsuke S. The Royal Society of Chemistry, 2011, 47(33): 9423.
[3] NIU Li-yuan, LIN Man-man, LI Xue, et al(牛丽媛, 林漫漫, 李 雪，等). Laser & Optoelectronics Progress(激光与光电子学进展), 2012, 49(6): 063001.
[4] Jagtiani A V, Sawant R, Carletta J. Measurement Science and Technology, 2008, 19(6): 1.
[5] Ismail H B, Havva T T, Hüseyin E G, et al. Royal Society of Chemsitry, 2015, 5: 56606.
[6] WU Juan-xia, XU Hua, ZHANG Jin(吴娟霞, 徐 华, 张 锦). Acta Chimica Sinica(化学学报), 2014, 72(3): 301.
[7] WANG Lei, GUO Shu-xia, DAI Yin-zhen, et al(王 磊, 郭淑霞, 戴吟臻，等). Chinese Journal of Analytical Chemistry(分析化学研究学报), 2015, 43(1): 33.
[8] Du P, Kibbe W A, Lin S M. Bioinformatics, 2006, 22(17): 2059.
[9] JIANG Yong-hua, MO Xiao-qiang, YOU Jia-yi, et al(蒋永华, 莫小强, 尤佳伊). China Measurement &Test(中国测试), 2013, 39(3).
[10] CHEN Yun-gu, SU Ben-yue(陈蕴谷, 苏本跃). Chinese Journal of Quantum Electronics(量子电子学报), 2012, 29(6): 665.
[11] FENG Lin, JING Yi-chen, MEI Lin-li. Journal of Propulsion and Power(推进与动力杂志), 2004, 20(2): 319.
[12] DENG Xian-lai, JI Guo-yi(邓先来, 纪国宜). Noise and Vibration Control(噪声与振动控制), 2012, 3: 72.
[13] JIANG Cheng-zhi, SUN Qiang, LIU Ying, et al(姜承志, 孙 强, 刘 英，等). Acta Optica Sinca(光学学报), 2014, 34(6): 299.
[14] LI Jin-rong, DAI Lian-kui, RUAN Hua(李津蓉, 戴连奎, 阮 华). CIESC Journal(化工学报), 2012, 63(7): 2128.
[15] LI Jin-rong, DAI Lian-kui, WU Xiao-li(李津蓉, 戴连奎, 武晓莉). Chinese Journal of Analytical Chemistry(分析化学), 2014, 42(10): 1518.
|
| [1] |
LI Jie, ZHOU Qu*, JIA Lu-fen, CUI Xiao-sen. Comparative Study on Detection Methods of Furfural in Transformer Oil Based on IR and Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 125-133. |
| [2] |
WANG Fang-yuan1, 2, HAN Sen1, 2, YE Song1, 2, YIN Shan1, 2, LI Shu1, 2, WANG Xin-qiang1, 2*. A DFT Method to Study the Structure and Raman Spectra of Lignin
Monomer and Dimer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 76-81. |
| [3] |
XING Hai-bo1, ZHENG Bo-wen1, LI Xin-yue1, HUANG Bo-tao2, XIANG Xiao2, HU Xiao-jun1*. Colorimetric and SERS Dual-Channel Sensing Detection of Pyrene in
Water[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 95-102. |
| [4] |
WANG Xin-qiang1, 3, CHU Pei-zhu1, 3, XIONG Wei2, 4, YE Song1, 3, GAN Yong-ying1, 3, ZHANG Wen-tao1, 3, LI Shu1, 3, WANG Fang-yuan1, 3*. Study on Monomer Simulation of Cellulose Raman Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 164-168. |
| [5] |
WANG Lan-hua1, 2, CHEN Yi-lin1*, FU Xue-hai1, JIAN Kuo3, YANG Tian-yu1, 2, ZHANG Bo1, 4, HONG Yong1, WANG Wen-feng1. Comparative Study on Maceral Composition and Raman Spectroscopy of Jet From Fushun City, Liaoning Province and Jimsar County, Xinjiang Province[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 292-300. |
| [6] |
LI Wei1, TAN Feng2*, ZHANG Wei1, GAO Lu-si3, LI Jin-shan4. Application of Improved Random Frog Algorithm in Fast Identification of Soybean Varieties[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3763-3769. |
| [7] |
WANG Zhi-qiang1, CHENG Yan-xin1, ZHANG Rui-ting1, MA Lin1, GAO Peng1, LIN Ke1, 2*. Rapid Detection and Analysis of Chinese Liquor Quality by Raman
Spectroscopy Combined With Fluorescence Background[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3770-3774. |
| [8] |
LIU Hao-dong1, 2, JIANG Xi-quan1, 2, NIU Hao1, 2, LIU Yu-bo1, LI Hui2, LIU Yuan2, Wei Zhang2, LI Lu-yan1, CHEN Ting1，ZHAO Yan-jie1*，NI Jia-sheng2*. Quantitative Analysis of Ethanol Based on Laser Raman Spectroscopy Normalization Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3820-3825. |
| [9] |
LU Wen-jing, FANG Ya-ping, LIN Tai-feng, WANG Hui-qin, ZHENG Da-wei, ZHANG Ping*. Rapid Identification of the Raman Phenotypes of Breast Cancer Cell
Derived Exosomes and the Relationship With Maternal Cells[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3840-3846. |
| [10] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
| [11] |
GUO He-yuanxi1, LI Li-jun1*, FENG Jun1, 2*, LIN Xin1, LI Rui1. A SERS-Aptsensor for Detection of Chloramphenicol Based on DNA Hybridization Indicator and Silver Nanorod Array Chip[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3445-3451. |
| [12] |
ZHU Hua-dong1, 2, 3, ZHANG Si-qi1, 2, 3, TANG Chun-jie1, 2, 3. Research and Application of On-Line Analysis of CO2 and H2S in Natural Gas Feed Gas by Laser Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3551-3558. |
| [13] |
LIU Jia-ru1, SHEN Gui-yun2, HE Jian-bin2, GUO Hong1*. Research on Materials and Technology of Pingyuan Princess Tomb of Liao Dynasty[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3469-3474. |
| [14] |
LI Wen-wen1, 2, LONG Chang-jiang1, 2, 4*, LI Shan-jun1, 2, 3, 4, CHEN Hong1, 2, 4. Detection of Mixed Pesticide Residues of Prochloraz and Imazalil in
Citrus Epidermis by Surface Enhanced Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3052-3058. |
| [15] |
ZHAO Ling-yi1, 2, YANG Xi3, WEI Yi4, YANG Rui-qin1, 2*, ZHAO Qian4, ZHANG Hong-wen4, CAI Wei-ping4. SERS Detection and Efficient Identification of Heroin and Its Metabolites Based on Au/SiO2 Composite Nanosphere Array[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3150-3157. |
|
|
|
|
