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Variational Mode Decomposition for Raman Spectral Denoising
Version 1
: Received: 17 July 2023 / Approved: 17 July 2023 / Online: 17 July 2023 (09:27:33 CEST)
A peer-reviewed article of this Preprint also exists.
Bian, X.; Shi, Z.; Shao, Y.; Chu, Y.; Tan, X. Variational Mode Decomposition for Raman Spectral Denoising. Molecules 2023, 28, 6406. Bian, X.; Shi, Z.; Shao, Y.; Chu, Y.; Tan, X. Variational Mode Decomposition for Raman Spectral Denoising. Molecules 2023, 28, 6406.
Abstract
As a fast and nondestructive spectroscopic analysis technique, Raman spectroscopy has been widely applied in chemistry. However, noise is usually unavoidable in Raman spectra. Hence, denoising is an important step before Raman spectral analysis. A novel spectral denoising method based on variational mode decomposition (VMD) was introduced to solve the above problem. The spectrum is decomposed into a series of modes (uk) by VMD. Then, the high frequency noise modes are removed and the remaining modes are reconstructed to obtain the denoised spectrum. The proposed method was verified by two artificial noised signals and two actual Raman spectra. As comparison, empirical mode decomposition (EMD), Savitzky-Golay (SG) smoothing and discrete wavelet transformation (DWT) are also investigated. At the same time, signal-to-noise ratio (SNR) was introduced as evaluation indicators to verify the performance of the proposed method. The results show that compared with EMD, VMD can significantly improve mode mixing and endpoint effect. Some information of the small sharp peak is lost after VMD denoising. However, VMD lost fewer information than that of EMD, SG smoothing and DWT. Moreover, the Raman spectrum by VMD denoising is more excellent than that of EMD, SG smoothing and DWT in terms of visualization and SNR. Therefore, VMD provides superior denoising capabilities for Raman spectra.
Keywords
Raman spectrum; Denoising; Variational mode decomposition; Empirical mode decomposition; Mode mixing
Subject
Chemistry and Materials Science, Analytical Chemistry
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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