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Denoising of Spectra by Adaptive Multiwindow Polynomial Fitting
Version 1
: Received: 7 August 2021 / Approved: 9 August 2021 / Online: 9 August 2021 (09:06:12 CEST)
How to cite: Charonov, S. Denoising of Spectra by Adaptive Multiwindow Polynomial Fitting. Preprints 2021, 2021080183 Charonov, S. Denoising of Spectra by Adaptive Multiwindow Polynomial Fitting. Preprints 2021, 2021080183
Abstract
A method for noise reduction of spectra based on the adaptive application of the Savitsky-Golay polynomial filter is presented. A polynomial approximation is calculated at all points of the spectrum and for all window sizes. The weighted sum of all polynomials containing the point to be processed is used as the result. The weighting factors are calculated by evaluating the quality of the fit. This paper proposes two evaluation functions. The performance of the presented method is compared with the Savitsky-Golay method and the wavelet noise reduction method. The proposed approach provides good noise reduction performance without using user-entered parameters.
Supplementary and Associated Material
http://www.geologie-lyon.fr/Raman/: Handbook of Raman Spectra for geology
https://doi.org/10.6084/m9.figshare.14899329: Data sets
https://spectralmultiplatform.blogspot.com/p/mathsmooth.html: Online version of an adaptive polynomial filter.
Keywords
Denoising; Savitzky-Golay filter; polynomial fitting
Subject
Computer Science and Mathematics, Probability and Statistics
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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