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Proceedings Paper

Detection and correction of noncalibrated spectral features in optical-spectra based on a wavelet-transformation
Author(s): Frank Vogt; Maurus Tacke
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Paper Abstract

12 Many spectroscopic monitoring techniques employ chemometric algorithms like principal component regression for calibration and evaluation of optical spectra. Systems based on this method, however, suffer from unknown spectral features appearing after calibration, which may result in major errors. The detection of non-calibrated absorption lines is important for treating errors in chemical processes. For these two reasons, the detection and classification of non-calibrated absorption features is of great importance in on-line spectroscopy. A novel approach is proposed here. A wavelet representation of principal components and measured spectra is shown to be appropriate for detection of non-calibrated spectral features. The algorithm can also be applied in combination with partial least-squares.

Paper Details

Date Published: 13 February 2001
PDF: 12 pages
Proc. SPIE 4201, Optical Methods for Industrial Processes, (13 February 2001); doi: 10.1117/12.417385
Show Author Affiliations
Frank Vogt, Fraunhofer-Institut fuer Physikalische Messtechnik (United States)
Maurus Tacke, FGAN-Forschungsinstitut fuer Optik (Germany)


Published in SPIE Proceedings Vol. 4201:
Optical Methods for Industrial Processes
Stuart Farquharson, Editor(s)

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