Working Paper Article Version 1 This version is not peer-reviewed

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://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

Comments (0)

We encourage comments and feedback from a broad range of readers. See criteria for comments and our Diversity statement.

Leave a public comment
Send a private comment to the author(s)
* All users must log in before leaving a comment
Views 0
Downloads 0
Comments 0
Metrics 0


×
Alerts
Notify me about updates to this article or when a peer-reviewed version is published.
We use cookies on our website to ensure you get the best experience.
Read more about our cookies here.