@article {Vickers:2001-04-01T00:00:00:0003-7028:389,
author = "Vickers, Thomas J. and Wambles, Ronald E. and Mann, Charles K.",
title = "Curve Fitting and Linearity: Data Processing in Raman Spectroscopy ",
journal = "Applied Spectroscopy",
volume = "55",
number = "4",
year = "2001-04-01T00:00:00",
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 *x*
^{2} 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.
",
pages = "389-393",
url = "http://www.ingentaconnect.com/content/sas/sas/2001/00000055/00000004/art00003",
doi = "doi:10.1366/0003702011952127",
keyword = "SMOOTHING, BACKGROUND REMOVAL, RAMAN SPECTROSCOPY"
}