Abstract：In X-ray fluorescence spectrometry (XRF) analysis, whether the background could be removed validly has considerable effect on the analysis accuracy. Because of the oscillation of real wavelet coefficients around the singularities and lack of shift-invariance, a novel background removing method based on approximately analytic complex wavelet transform is presented. The complex wavelet is implemented through two real wavelets, so it has real wavelet’s main properties that are time-frequency localization and multi-resolution analysis. The spectrum is decomposed with the complex wavelet, and then the background is obtained through the low frequency approximation. In order to test its effectiveness, the algorithm is used to extract the backgrounds of one simulated spectrum and one experimental spectrum. The effect to the desired information, such as net peak areas and peak positions, is also considered. Experiments results show the backgrounds obtained through the proposed complex wavelet transform are more accurate than common real wavelet transform. A conclusion could be drawn that the proposed algorithm could remove the background accurately while keeping the desired information intact.
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