Patent Document ID: 7693689
Application ID: 11960803
Patent Status: 1

Claim One:
1. A noise-component removing method for removing a noise component from multipoint spectral data that has been generated through measurements performed at measurement points of a sample surface, the method comprising: a concentration-variable calculation step of calculating, as a concentration variable to be used in partial least squares regression, a value obtained by quantifying characteristic information about a characteristic of each measurement point, other than spectral information of the measurement point; a partial least square (PLS) analysis step of determining components of the multipoint spectral data for each measurement point in a descending order of eigenvalues of the components by subjecting the multipoint spectral data to multivariate analysis based on the partial least squares regression using the value calculated in the concentration-variable calculation step as the concentration variable to be used in the partial least squares regression and using the spectral information as an independent variable in the partial least squares regression; and a spectrum reconstruction step of reconstructing, using the processor, the multipoint spectral data for each measurement point to eliminate a component having an eigenvalue lower than a predetermined value, from the components determined in the PLS analysis step.