baseline_lsp: Least-Squares Polynomial

In ChristianGoueguel/specProc: Preprocessing Tools For Laser-Induced Breakdown Spectroscopy (LIBS) Spectra

Least-Squares Polynomial

Description

This function performs baseline correction on the spectral matrix by estimating and removing the continuous background emission using least-squares polynomial curve fitting approach.

Usage

baseline_lsp(x, degree = 4, tol = 0.001, max.iter = 10)

Arguments

x	A matrix or data frame.
degree	An integer specifying the degree of the polynomial fitting function. The default value is 4.
tol	A numeric value representing the tolerance for the difference between iterations. The default value is 1e-3.
max.iter	An integer specifying the maximum number of iterations for the algorithm. The default value is 10.

Details

This function implements the algorithm described in Lieber and Mahadevan-Jansen (2003), which smoothes the spectrum in such a way that peaks are automatically eliminated, leaving only the baseline to be subtracted from the raw spectrum. The basis for this method is a modified least-squares-based polynomial curve-fitting function, such that all data points in the generated curve that have an intensity value higher than their respective pixel value in the input spectrum are automatically reassigned to the original intensity.

Value

A list with two elements:

• correction: The baseline-corrected spectral matrix.

• background: The fitted background emission.

Author(s)

Christian L. Goueguel

References

• Lieber, C.A., Mahadevan-Jansen, A., (2003). Automated method for subtraction of fluorescence from biological Raman spectra. Applied Spectroscopy, 57(11):1363-1367

ChristianGoueguel/specProc documentation built on Nov. 9, 2024, 3:23 p.m.