• Acta Optica Sinica
  • Vol. 42, Issue 22, 2230001 (2022)
Ganshang Si1、2, Jiaxiang Liu1, Zhengang Li1、2, Zhiqiang Ning1、2, and Yonghua Fang1、2、*
Author Affiliations
  • 1Key Laboratory of Environmental Optics and Technology, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, Anhui , China
  • 2University of Science and Technology of China, Hefei 230026, Anhui , China
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    DOI: 10.3788/AOS202242.2230001 Cite this Article Set citation alerts
    Ganshang Si, Jiaxiang Liu, Zhengang Li, Zhiqiang Ning, Yonghua Fang. Fluorescence Background Subtraction Algorithm of UV Raman Based on Morphology and Polynomial Fitting[J]. Acta Optica Sinica, 2022, 42(22): 2230001 Copy Citation Text show less
    Raman and fluorescence spectral ranges (excitation light wavelength is 266 nm)
    Fig. 1. Raman and fluorescence spectral ranges (excitation light wavelength is 266 nm)
    Baseline correction. (a) Morphological algorithm; (b) polynomial fitting algorithm
    Fig. 2. Baseline correction. (a) Morphological algorithm; (b) polynomial fitting algorithm
    Baseline correction based on morphology and polynomial joint
    Fig. 3. Baseline correction based on morphology and polynomial joint
    Comparison of correction effects for different baselines using different methods. (a) Sine function; (b) Gaussian function;(c) Sigmoid function; (d) logarithmic function
    Fig. 4. Comparison of correction effects for different baselines using different methods. (a) Sine function; (b) Gaussian function;(c) Sigmoid function; (d) logarithmic function
    Influence of parameter setting on baseline correction effect
    Fig. 5. Influence of parameter setting on baseline correction effect
    Sample preparation and experimental device. (a) Sample preparation; (b) UV Raman spectroscopy setup
    Fig. 6. Sample preparation and experimental device. (a) Sample preparation; (b) UV Raman spectroscopy setup
    Original spectra of potassium nitrate samples on different substrates
    Fig. 7. Original spectra of potassium nitrate samples on different substrates
    Results of baseline correction of potassium nitrate powder on different substrates obtained by Mor+poly and airPLS algorithms. (a) Paper; (b) transparent acrylic sheet; (c) blue acrylic sheet; (d) metal aluminum
    Fig. 8. Results of baseline correction of potassium nitrate powder on different substrates obtained by Mor+poly and airPLS algorithms. (a) Paper; (b) transparent acrylic sheet; (c) blue acrylic sheet; (d) metal aluminum
    Numberabc
    11401205
    21035010
    3405506
    410750120
    51508808
    Table 1. Parameters of Gaussian function
    Baseline typeParameterImorModpolyairPLSMor+poly
    SineOptimal parametersw=25n=6w=25, n=6
    RMSE0.3051.1150.2040.134
    GaussianOptimal parametersw=25n=8w=25, n=8
    RMSE1.0682.5371.0411.032
    SigmoidOptimal parametersw=25n=8w=25, n=8
    RMSE1.0651.3890.2810.256
    LogarithmOptimal parametersw=25n=7w=25, n=7
    RMSE0.3941.0710.3720.322
    Table 2. Comparison of baseline correction effects of different methods
    Raman spectrum of different substratesStdev of airPLS algorithmStdev of Mod+poly algorithm
    Paper10.409.37
    Acrylic-transparent32.0723.17
    Acrylic-blue22.0713.12
    Metal aluminum13.7511.65
    Table 3. Comparison of Stdev after baseline correction by different methods
    Ganshang Si, Jiaxiang Liu, Zhengang Li, Zhiqiang Ning, Yonghua Fang. Fluorescence Background Subtraction Algorithm of UV Raman Based on Morphology and Polynomial Fitting[J]. Acta Optica Sinica, 2022, 42(22): 2230001
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