AUTHOR=Bian Xihui , Ling Mengxuan , Chu Yuanyuan , Liu Peng , Tan Xiaoyao TITLE=Spectral denoising based on Hilbert–Huang transform combined with F-test JOURNAL=Frontiers in Chemistry VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/chemistry/articles/10.3389/fchem.2022.949461 DOI=10.3389/fchem.2022.949461 ISSN=2296-2646 ABSTRACT=

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.