Smoothing of spectral data in the Fourier domain

Smoothing of spectral data using Fourier transforms is described and demonstrated with Lorentzian, sinc(2), and sine smoothing functions. Four parameters are defined and used to study the smoothing operation. It is also concluded that the best smoothing function is a sinc function if we require that...

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Bibliographic Details
Published inApplied optics (2004) Vol. 21; no. 10; p. 1866
Main Authors Kauppinen, J K, Moffatt, D J, Mantsch, H H, Cameron, D G
Format Journal Article
LanguageEnglish
Published United States 15.05.1982
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Summary:Smoothing of spectral data using Fourier transforms is described and demonstrated with Lorentzian, sinc(2), and sine smoothing functions. Four parameters are defined and used to study the smoothing operation. It is also concluded that the best smoothing function is a sinc function if we require that the distortions due to the smoothing operation are smaller than the residual noise. Sine smoothing using Fourier transforms is also compared to least square smoothing in the frequency domain, and the advantages of sine smoothing are illustrated.
ISSN:1559-128X
DOI:10.1364/AO.21.001866