Multiplicative Scatter Correction (msc)

This function implements the multiplicative scatter correction method which attempts to remove physical light scatter by accounting for additive and multiplicative effects (Geladi et al., 1985).

Usage

msc(X, ref_spectrum = colMeans(X))

Arguments

X: a numeric matrix of spectral data.
ref_spectrum: a numeric vector corresponding to an "ideal" reference spectrum (e.g. free of scattering effects). By default the function uses the mean spectrum of the input X. See details. Note that this argument was previously named as reference_spc, however, it has been renamed to ref_spectrum to emphasize that this argument is a vector and not a matrix of spectra.

Value

a matrix of normalized spectral data with an attribute which indicates the reference spectrum used.

Details

The Multiplicative Scatter Correction (MSC) is a normalization method that attempts to account for additive and multiplicative effects by aligning each spectrum (\(x_i\)) to an ideal reference one (\(x_r\)) as follows:

\[x_i = m_i x_r + a_i\] \[MSC(x_i) = \frac{x_i - a_i}{m_i}\]

where \(a_i\) and \(m_i\) are the additive and multiplicative terms respectively.

References

Geladi, P., MacDougall, D., and Martens, H. 1985. Linearization and Scatter-Correction for Near-Infrared Reflectance Spectra of Meat. Applied Spectroscopy, 39(3):491-500.

Author

Leonardo Ramirez-Lopez and Guillaume Hans

Examples

data(NIRsoil)
NIRsoil$msc_spc <- msc(X = NIRsoil$spc)

# 10 first msc spectra
matplot(
  x = as.numeric(colnames(NIRsoil$msc_spc)),
  y = t(NIRsoil$msc_spc[1:10, ]),
  type = "l",
  xlab = "wavelength, nm",
  ylab = "msc"
)


# another example
spectra_a <- NIRsoil$spc[1:40, ]
spectra_b <- NIRsoil$spc[-(1:40), ]

spectra_a_msc <- msc(spectra_a, colMeans(spectra_a))

# correct spectra_a based on the reference spectrum used to correct
# spectra_a

spectra_b_msc <- msc(
  spectra_b,
  ref_spectrum = attr(spectra_a_msc, "Reference spectrum")
)