4.6 Article

Searching for Alternatives to the Savitzky-Golay Filter in the Spectral Processing Domain

期刊

APPLIED SPECTROSCOPY
卷 77, 期 4, 页码 426-432

出版社

SAGE PUBLICATIONS INC
DOI: 10.1177/00037028231154278

关键词

Signal processing; data smoothing; noise reduction; numerical differentiation; Savitzky-Golay filter; fast Fourier transform; FFT

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The Savitzky-Golay filter concept, proposed by Savitzky and Golay, is an elegant and effective tool in spectra processing. Despite its limitations, it has become widely adopted and is considered superior to alternative approaches in many fields.
An elegant, well-established effective data filter concept, proposed originally by Abraham Savitzky and Marcel J.E. Golay, is undoubtedly a very effective tool, however not free from limitations and drawbacks. Despite the latter, over the years it has become a monopolist in many fields of spectra processing, claiming a commercial superiority over alternative approaches, which would potentially allow to obtain equivalent or in some cases even more reliable results. In order to show that basic operations performed on spectral datasets, like smoothing or differentiation, do not have to be equated to the application of the one particular single algorithm, several of such alternatives are briefly presented within this paper and discussed with regard to their practical realization. A special emphasis is put on the fast Fourier methodology (FFT), being widespread in the general domain of signal processing. Finally, a user-friendly Matlab routine, in which the outlined algorithms are implemented, is shared, so that one can select and apply the technique of spectral data processing more adequate for their individual requirements without the need to code it prior to use.

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