Wavelet analysis of high and low resolution gamma-ray spectra: An investigation of peak finding techniques

Abstract

For the detection of radiological materials, peak identification within gamma spectroscopy data is a useful tool. This paper discusses the application of wavelet analysis as a peak finding technique to high resolution data recorded by high purity germanium (HPGe) detectors. Whilst the wavelet method has been previously applied to high efficiency/low resolution data, this work considers the applicability of wavelet analysis to high resolution spectral datasets with varying levels of background. An algorithm has been developed that automatically locates wavelet transform modulus maxima (WTMM) lines; the method identifies local maxima and minima of the scalogram joining data points within the same potential. The approach was applied to analyse a range of experimental recorded radiation spectra, both from shielded and un-shielded sources. Peak locations were found by comparing peak widths with those expected based on the detector resolution function (DRF), alongside WTMM straightness and line length filter tests. Findings indicated that, when implemented in this approach, the wavelet analysis method was applicable to the identification of high-resolution photopeaks when concealed within varying levels of background.