Applications of wavelet analyses on spectroscopic experiments

Wavelet transform is an innovative and powerful tool for analyzing complex data such as those obtained by spectroscopic techniques. In particular, it allows to locally resolve a non-stationary signal by means of functions called mother wavelets so producing a time-scale view of the signal. In addition, thanks to the wavelet multiscaling properties it is possible to get information both on a global and on a local view, to characterize transitory signal characteristics, trends, drifts, spectra abrupt changes and to perform signal denoising. The aim of this chapter is to highlight how wavelet transform can be effectively employed to extract precious information from experimental results obtained by spectroscopic techniques, such as Infrared, light and neutron scattering spectroscopies. In particular, it will be shown how it is possible to characterize, following different approaches, the registered spectral profiles as well as, by means of Wavelet Cross Correlation, to evaluate spectra and images similarity degree