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Wavelet decompositions of Raman spectra were investigated with respect to their usability for spike removal and denoising of the raw data. It could be shown that those operations should be performed sequentially. Suppression of spikes is not straightforwardly possible by wavelet transformation; however, the wavelet transform may be used to recognize the spikes by their first level detail coefficients. Spike locations could be projected from the details to the approximations and, further, to appropriate locations of the original spectrum. After spike recognition, those regions will be replaced by interpolated values. To complete processing, denoising is performed with the despiked spectrum by repeated application of wavelet transform methods.

The wavelet transform has been established with the Fourier transform as a data-processing method in analytical chemistry. The main fields of application in analytical chemistry are related to denoising, compression, variable reduction, and signal suppression. Analytical applications were selected showing prospects and limitations of the wavelet transform. An important aspect consists in showing the advantage of wavelet transform over Fourier transform with respect to dual localization of a signal in both the original and the transformed domain enabling principal new application fields in comparison with Fourier transform.

A computer-program "IR-Spectroscopy" for the interpretation of infrared spectra of organic compounds is described. It contains the following basic items for preprocessing and execution of the computer based interpretation process: handling of the rule-base CorTab, routines for automatic rule generation and interpretation modules on the basis of the programming languages PROLOG and C.

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