Authors: Vickers, Thomas J.; Wambles, Ronald E.; Mann, Charles K.

Source: Applied Spectroscopy, Volume 55, Issue 4, Pages 138A-152A and 373-516 (April 2001) , pp. 389-393(5)

Publisher: Society for Applied Spectroscopy

Abstract:

A study has been made of the use of polynomial curve fitting for removal of nonlinear background and high-spatial-frequency noise components from Raman spectra. Two variations on polynomial curve fitting through a least-squares calculation are used. One, involving fitting data x values to corresponding y values, was used to approximate background functions, which are subtracted from the original data. For smoothing, a reference matrix of six vectors that contains a unity d.c. level, a ramp made up of x values, a quadratic made up of x² values, etc., is fitted to a section of data. The reference vectors are scaled by the fit values and added to give the smoothed estimate of a spectral peak. It is demonstrated, with factor analysis as a test procedure, that the background removal procedure does remove nonlinearities that were present in the original data. The smoothing procedure rejects high-spatial-frequency noise without introducing detectable nonlinearities.

Keywords: RAMAN SPECTROSCOPY; BACKGROUND REMOVAL; SMOOTHING

Document Type: Research article

DOI: http://dx.doi.org/10.1366/0003702011952127

Affiliations: 1: Department of Chemistry, Florida State University, Tallahassee, Florida 32306-4390

Publication date: 2001-04-01

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