Laser & Optoelectronics Progress, Volume. 58, Issue 7, 0730001(2021)
Denoising of Digital Filtering Based on Wavelength Modulation Spectroscopy
Fig. 1. Wavelet transform decomposition flow chart
Fig. 2. Principle of Gabor transform for signal denoising
Fig. 3. Simulated NH3 spectral signal.(a)Original second harmonic (2f) signal;(b)Gaussian noise;(c)noised second harmonic signal
Fig. 4. SNR as a function of parameters in different methods. (a) SNR as a function of decomposition level in wavelet transform; (b) SNR as a function of threshold value in Gabor transform
Fig. 5. RMSE after denoising. (a) Wavelet transform denoising; (b) Gabor transform denoising
Fig. 6. Second harmonic (2f) signal after denoising. (a) Wavelet transformation denoising; (b) Gabor transformation denoising
Fig. 7. System for measuring low concentration NH3
Fig. 8. Noisy second harmonic signals
Fig. 9. Second harmonic signals of different concentrations of NH3 after denoising. (a) Wavelet transform denoising;(b) Gabor transform denoising
Fig. 10. Linear relationship between peak height of second harmonic signal of different concentrations of NH3 and measured concentration. (a) Wavelet transform; (b) Gabor transform
Get Citation
Copy Citation Text
Lifang Zhang, Fei Wang, Hao Wei, Jing Wang, Haibin Cui, Guanjia Zhao. Denoising of Digital Filtering Based on Wavelength Modulation Spectroscopy[J]. Laser & Optoelectronics Progress, 2021, 58(7): 0730001
Category: Spectroscopy
Received: Oct. 9, 2020
Accepted: Nov. 18, 2020
Published Online: Apr. 25, 2021
The Author Email: Zhang Lifang (21227023@zju.edu.cn)