Method for terahertz time-domain spectral analysis based on wavelet transform

被引：0
作者：
Yu, Qian [1 ]
Zhao, Yuejin [1 ]
Yu, Fei [1 ]
Liu, Xiaohua [1 ]
Zhang, Liangliang [1 ]
Dong, Liquan [1 ]
机构：
[1] Department of Optical Engineering, Beijing Institute of Technology
来源：
Guangxue Xuebao/Acta Optica Sinica | 2009年 / 29卷 / 03期
关键词：
Spectral analysis; Spectroscopy; Terahertz; Wavelet multi-resolution entropy; Wavelet transform;
D O I：
10.3788/AOS20092903.0838
中图分类号：
学科分类号：
摘要：
The conventional terahertz spectral analysis based on Fourier transform needs to measure the terahertz reference signal without simples, and the terahertz spectra measurement is required in nitrogen. A novel method for terahertz time-domain spectral analysis based on wavelet transform is proposed to reduce terahertz spectral measurement steps. Firstly, the de-noising process about the spectroscopic data of the sample is achieved, and then the multi-scale wavelet-transform is realized by Coiflets wavelet base. The wavelet multi resolution entropies of samples under different wavelet decomposition scales are calculated, and the characteristic information describing samples is obtained directly. The experimental results indicate that the wavelet multi-resolution entropies, which are observably different between different samples but adequately stable between the same samples, can provide a valid quantitative criterion for the materials recognition. Spectral signal's wavelet multi-resolution entropies have good repetition in different humidity, and the average variance of the wavelet multi-resolution entropies is smaller than 0.05.
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页码：838 / 843
页数：5
相关论文
共 13 条
  • [1] Li F., Ren R., Wang X., Et al., The theory and some applications of terahertz radiation, Laser & Infrared, 36, SUPPL., pp. 785-791, (2006)
  • [2] Li M., Fortin J., Kim J.Y., Et al., Dielectric constant measurement of thin films using goniometric terahertz time-domain spectroscopy, Quant. Electron., IEEE, 7, 4, pp. 624-629, (2001)
  • [3] Zhao H., Ge M., Wang W., Et al., Application of terahertz time-dome in spectroscopy in chemistry and biology, Chemistry, 6, 2, pp. 87-90, (2005)
  • [4] Zhang L., Zhang C., Zhao Y., Et al., Time-resolved terahertz spectroscopy of explosives, Spectroscopy and Spectral Analysis, 27, 8, pp. 1457-1460, (2007)
  • [5] Zhou W., Gui L., Zhou L., Et al., Wavelet Analysis Advanced Technology, pp. 87-99, (2006)
  • [6] Yang Z., Dai Y., Wang G., Use of wavelet in specifying optics, Chin. Opt. Lett., 5, 1, pp. 44-46, (2007)
  • [7] Fu W., Xu S., An improved algorithm for de-noising in wavelet transform domain, Computer Engineering and Applications, 42, 11, pp. 80-84, (2006)
  • [8] Tan Y., Tian J., Liu J., Adaptively wavelet-based image denoising algorithm with edge preserving, Chin. Opt. Lett., 4, 2, pp. 80-83, (2006)
  • [9] Zeng G., Zhao R., Image denoising using least squares wavelet support vector machines, Chin. Opt. Lett., 5, 11, pp. 632-635, (2007)
  • [10] Li S., Xie P., Li Y., Et al., Wavelet transform based differential optical absorption spectroscopy data processing, Acta Optica Sinica, 26, 11, pp. 1601-1603, (2006)
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