| 光谱学与光谱分析 |
|
|
|
|
|
| A Denoising Algorithm for Absorption Spectra by Wavelet Transform Modulus Maxima Shift-Related Filter |
| TAO Wei-liang1,WANG Xian-pei1,LIU Yan2,YUAN Lei3 |
1. Laboratory of System Integration and Faults Diagnostics, Wuhan University, Wuhan 430079, China
2. School of Electronic Information, Wuhan University, Wuhan 430079, China
3. Department of Electric and Information Engineering, Xiangfan University, Xiangfan 441053, China |
|
|
|
|
Abstract In the present paper, a wavelet modulus maximum shift-related filter algorithm is proposed for denoising the absorption spectra. Firstly, using the wavelet transform modulus maxima theory, useful signal components and noise components of the binary wavelet coefficients of absorption spectra are identified. Then, the useful signal components are aligned in the wave number domain to correct the “drifting” of modulus maximum across the scales, and the noise components are smoothed. Finally, according to the wavelet interscale dependencies obtained by multiplying the adjacent wavelet subbands preprocessed by the above procedure, important features of signal are enhanced while noises are attenuated further. Compared with the traditional spatially selective noise filtration technique proposed by Xu et al and adaptive multiscale products thresholding technique proposed by Paul Bao et al, the proposed wavelet modulus maximum shift-related filter algorithm has several advantages. First, it does not need estimate of the noise intensity, which could avoid the error introducing and the complex calculation. Meanwhile, there is not iterative calculation in the proposed algorithm, which could eliminate the risk of slow convergence or no convergence of the algorithm. Furthermore, the “drifting” of modulus maximum across the scales could be corrected in the proposed algorithm, which could make up for the loss of the spectrum information caused by the “drifting” phenomenon. Experiments show that the proposed scheme can effectively suppress noise and preserve the useful components in the infrared absorption spectra of SF6 gas.
|
|
Received: 2008-03-16
Accepted: 2008-06-18
|
|
|
|
Corresponding Authors:
TAO Wei-liang
E-mail: taowl2003@163.com
|
|
[1] ZHENG Hua, WANG Li-qiang, SHI Yan, et al(郑 华，王立强，石 岩，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2008, 28(5): 1126.
[2] PENG Dan, XU Ke-xin, LI Chen-xi(彭 丹，徐可欣，李晨曦). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2008, 28(4): 825.
[3] GUO Hao-yan, HU Shao-ming, QUAN Guang-ri(郭暤岩，胡绍明，权光日). Computer Engineering and Design(计算机工程与设计), 2007, 28(7): 1504.
[4] YING Yi-bin, LIU Yan-de, FU Xia-ping(应义斌，刘燕德，傅霞萍). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(1): 63.
[5] HE Chang-wei, LIU Ying-xia, REN Wen-jie, et al(贺长伟，刘英霞，任文杰，等). Computer Applications(计算机应用), 2007, 27(9): 2117.
[6] FAN Lei, HUANG Shuang-hua(范 磊，黄双华). Ship Electronic Engineering(舰船电子工程), 2008, (5): 104.
[7] ZHAO Rui-zhen, HU Zhan-yi, HU Shao-hai(赵瑞珍，胡占义，胡绍海). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(8): 1644.
[8] 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.
[9] Mallat S, Zhong S, IEEE Trans. Pattern Anal. Machine Intell., 1992, 14(7): 710.
[10] WU Li-qing, LI Bo, LIU Run-hua(吴荔清，李 波，刘润华). Science Technology and Engineering(科学技术与工程), 2008, 8(9): 2450.
[11] YUAN Hua, ZHANG Wei-ning, LU Jun, et al(袁 华，张卫宁，路 峻，等). Journal of System Simulation(系统仿真学报), 2005, 17(4): 838.
[12] Xu Y, Weaver J B, Healy Jr D M, et al. IEEE Trans. Image Processing, 1994, 3: 747.
[13] Paul Bao, Lei Zhang, IEEE Transactions On Medical Imaging, 1994, 22(9): 1089.
[14] Pan Quan, Zhang Lei, Dai Guanzhong, et al. IEEE Transactions on Signal Processing, 1999, 47(12): 3401.
[15] Mallat S, Hwang W L. IEEE Trans. on Information Theory, 1992, 38(2): 617.
[16] Meyer Y, Wavelets and Operators. Cambridge, U.K.: Cambridge Univ. Press, 1992. |
| [1] |
MA Ping1, 2, Andy Hsitien Shen1*, ZHONG Yuan1, LUO Heng1. Study on UV-Vis Absorption Spectra of Jadeite From Different Origins[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1827-1831. |
| [2] |
ZHOU Cai-hua, DING Xiao. DFT Calculation of Absorption Spectra for Planar Porphyrin Derivatives[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1769-1773. |
| [3] |
LI Shu-jie1, LIU Jie1, DENG Zi-ang1, OU Quan-hong1, SHI You-ming2, LIU Gang1*. Study of Germinated Rice Seeds by FTIR Spectroscopy Combined With Curve Fitting[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1832-1840. |
| [4] |
ZHANG Yan-ru1, 2, SHAO Peng-shuai1*. Study on the Effects of Planting Years of Vegetable Greenhouse on the
Cucumber Qualties Using Mid-IR Spectroscopoy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1816-1821. |
| [5] |
SHI Wen-qiang1, XU Xiu-ying1*, ZHANG Wei1, ZHANG Ping2, SUN Hai-tian1, 3, HU Jun1. Prediction Model of Soil Moisture Content in Northern Cold Region Based on Near-Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1704-1710. |
| [6] |
WANG Yue1, 3, 4, CHEN Nan1, 2, 3, 4, WANG Bo-yu1, 5, LIU Tao1, 3, 4*, XIA Yang1, 2, 3, 4*. Fourier Transform Near-Infrared Spectral System Based on Laser-Driven Plasma Light Source[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1666-1673. |
| [7] |
FENG Rui-jie1, CHEN Zheng-guang1, 2*, YI Shu-juan3. Identification of Corn Varieties Based on Bayesian Optimization SVM[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1698-1703. |
| [8] |
YU Zhi-rong, HONG Ming-jian*. Near-Infrared Spectral Quantitative Analysis Network Based on Grouped Fully Connection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1735-1740. |
| [9] |
XIE Yu-yu1, 2, 3, HOU Xue-ling1, CHEN Zhi-hui2, AISA Haji Akber1, 3*. Density Functional Theory Studies on Structure and Spectra of Salidroside Molecule[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1786-1791. |
| [10] |
MENG Fan-jia1, LUO Shi1, WU Yue-feng1, SUN Hong1, LIU Fei2, LI Min-zan1*, HUANG Wei3, LI Mu3. Characteristic Extraction Method and Discriminant Model of Ear Rot of Maize Seed Base on NIR Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1716-1720. |
| [11] |
PENG Yan-fang1, WANG Jun1, WU Zhi-sheng2*, LIU Xiao-na3, QIAO Yan-jiang2*. NIR Band Assignment of Tanshinone ⅡA and Cryptotanshinone by
2D-COS Technology and Model Application Tanshinone Extract[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1781-1785. |
| [12] |
TIAN Xue1, CHE Qian1, YAN Wei-min1, OU Quan-hong1, SHI You-ming2, LIU Gang1*. Discrimination of Millet Varieties and Producing Areas Based on Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1841-1847. |
| [13] |
WANG Xue-pei1, 2, ZHANG Lu-wei1, 2, BAI Xue-bing3, MO Xian-bin1, ZHANG Xiao-shuan1, 2*. Infrared Spectral Characterization of Ultraviolet Ozone Treatment on Substrate Surface for Flexible Electronics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1867-1873. |
| [14] |
JIANG Rong-chang1, 2, GU Ming-sheng2, ZHAO Qing-he1, LI Xin-ran1, SHEN Jing-xin1, 3, SU Zhong-bin1*. Identification of Pesticide Residue Types in Chinese Cabbage Based on Hyperspectral and Convolutional Neural Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1385-1392. |
| [15] |
WANG Zhong, WAN Dong-dong, SHAN Chuang, LI Yue-e, ZHOU Qing-guo*. A Denoising Method Based on Back Propagation Neural Network for
Raman Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1553-1560. |
|
|
|
|
