Spectral denoising based on Hilbert–Huang transform combined with F-test
Due to the influence of uncontrollable factors such as the environment and instruments, noise is unavoidable in a spectral signal, which may affect the spectral resolution and analysis result. In the present work, a novel spectral denoising method is developed based on the Hilbert–Huang transform (H...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-08-01
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| Series: | Frontiers in Chemistry |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fchem.2022.949461/full |
| _version_ | 1811188680575942656 |
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| author | Xihui Bian Xihui Bian Xihui Bian Mengxuan Ling Mengxuan Ling Mengxuan Ling Yuanyuan Chu Peng Liu Xiaoyao Tan |
| author_facet | Xihui Bian Xihui Bian Xihui Bian Mengxuan Ling Mengxuan Ling Mengxuan Ling Yuanyuan Chu Peng Liu Xiaoyao Tan |
| author_sort | Xihui Bian |
| collection | DOAJ |
| description | Due to the influence of uncontrollable factors such as the environment and instruments, noise is unavoidable in a spectral signal, which may affect the spectral resolution and analysis result. In the present work, a novel spectral denoising method is developed based on the Hilbert–Huang transform (HHT) and F-test. In this approach, the original spectral signal is first decomposed by empirical mode decomposition (EMD). A series of intrinsic mode functions (IMFs) and a residual (r) are obtained. Then, the Hilbert transform (HT) is performed on each IMF and r to calculate their instantaneous frequencies. The mean and standard deviation of instantaneous frequencies are calculated to further illustrate the IMF frequency information. Third, the F-test is used to determine the cut-off point between noise frequency components and non-noise ones. Finally, the denoising signal is reconstructed by adding the IMF components after the cut-off point. Artificially chemical noised signal, X-ray diffraction (XRD) spectrum, and X-ray photoelectron spectrum (XPS) are used to validate the performance of the method in terms of the signal-to-noise ratio (SNR). The results show that the method provides superior denoising capabilities compared with Savitzky–Golay (SG) smoothing. |
| first_indexed | 2024-04-11T14:22:23Z |
| format | Article |
| id | doaj.art-a7e75570de964cb298bc4ef5759fe926 |
| institution | Directory Open Access Journal |
| issn | 2296-2646 |
| language | English |
| last_indexed | 2024-04-11T14:22:23Z |
| publishDate | 2022-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Chemistry |
| spelling | doaj.art-a7e75570de964cb298bc4ef5759fe9262022-12-22T04:19:00ZengFrontiers Media S.A.Frontiers in Chemistry2296-26462022-08-011010.3389/fchem.2022.949461949461Spectral denoising based on Hilbert–Huang transform combined with F-testXihui Bian0Xihui Bian1Xihui Bian2Mengxuan Ling3Mengxuan Ling4Mengxuan Ling5Yuanyuan Chu6Peng Liu7Xiaoyao Tan8Key Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, ChinaKey Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Sichuan, ChinaState Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, ChinaKey Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, ChinaKey Lab of Process Analysis and Control of Sichuan Universities, Yibin University, Sichuan, ChinaState Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining, ChinaKey Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, ChinaKey Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, ChinaKey Laboratory of Separation Membranes and Membrane Processes, School of Chemical Engineering and Technology, Tiangong University, Tianjin, ChinaDue to the influence of uncontrollable factors such as the environment and instruments, noise is unavoidable in a spectral signal, which may affect the spectral resolution and analysis result. In the present work, a novel spectral denoising method is developed based on the Hilbert–Huang transform (HHT) and F-test. In this approach, the original spectral signal is first decomposed by empirical mode decomposition (EMD). A series of intrinsic mode functions (IMFs) and a residual (r) are obtained. Then, the Hilbert transform (HT) is performed on each IMF and r to calculate their instantaneous frequencies. The mean and standard deviation of instantaneous frequencies are calculated to further illustrate the IMF frequency information. Third, the F-test is used to determine the cut-off point between noise frequency components and non-noise ones. Finally, the denoising signal is reconstructed by adding the IMF components after the cut-off point. Artificially chemical noised signal, X-ray diffraction (XRD) spectrum, and X-ray photoelectron spectrum (XPS) are used to validate the performance of the method in terms of the signal-to-noise ratio (SNR). The results show that the method provides superior denoising capabilities compared with Savitzky–Golay (SG) smoothing.https://www.frontiersin.org/articles/10.3389/fchem.2022.949461/fulldenoisingHilbert–Huang transformempirical mode decompositionx-ray diffractionx-ray photoelectron spectrumf-test |
| spellingShingle | Xihui Bian Xihui Bian Xihui Bian Mengxuan Ling Mengxuan Ling Mengxuan Ling Yuanyuan Chu Peng Liu Xiaoyao Tan Spectral denoising based on Hilbert–Huang transform combined with F-test Frontiers in Chemistry denoising Hilbert–Huang transform empirical mode decomposition x-ray diffraction x-ray photoelectron spectrum f-test |
| title | Spectral denoising based on Hilbert–Huang transform combined with F-test |
| title_full | Spectral denoising based on Hilbert–Huang transform combined with F-test |
| title_fullStr | Spectral denoising based on Hilbert–Huang transform combined with F-test |
| title_full_unstemmed | Spectral denoising based on Hilbert–Huang transform combined with F-test |
| title_short | Spectral denoising based on Hilbert–Huang transform combined with F-test |
| title_sort | spectral denoising based on hilbert huang transform combined with f test |
| topic | denoising Hilbert–Huang transform empirical mode decomposition x-ray diffraction x-ray photoelectron spectrum f-test |
| url | https://www.frontiersin.org/articles/10.3389/fchem.2022.949461/full |
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