A background elimination method based on wavelet transform for Raman spectra

A new hybrid algorithm is proposed to eliminate the varying background of spectral signals. The method is based on the use of multi-resolution, which is one of the main advantages provided by wavelet transform. Compared with the analyte signal, the background has a low frequency. The new method firstly split the signals into different frequency components, and then removes the varying low-frequency background. The method is successfully applied to simulated spectral data set and experimental Raman spectral data. The results showed that the wavelet transform technique could handle all kinds of background and low signal-to-background ratio spectra, and required no prior knowledge about the sample composition, no selection of suitable background correction points, and no mathematical assumption of the background distribution. The proposed procedure was illustrated, by processing real spectra, to be an effective and practical tool for background elimination in Raman spectra. In addition, the proposed strategy can be applied to other spectral signals as well.