Abstract
Automatic peak detection is important for the application of Raman spectroscopy. However, the existence of noise and baseline disturbances will greatly degrade the reliability and accuracy of the peak detection. In this paper we proposed a hybrid wavelet-transform-based algorithm to improve the peak detection performance. Here, continuous wavelet transform method was used to robustly identify the spectral peaks, and to minimize the influence of noise and baseline disturbances. A localized curve-fitting method was used to obtain the accurate parameters of the peaks, such as location, width and intensity. The simulation and experiment proved that this method was robust against various disturbances and it could not only automatically detect the peaks but also obtain accurate parameters of the spectral peaks.
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