A new approach in the detection of weak {\gamma}-ray peak of the   radioactive waste in tomography {\gamma} scanning
  We demonstrate a new approach to efficiently detect weak {\gamma}-ray peak of the radioactive waste in tomographic {\gamma} scanning (TGS). In the TGS measurement, {\gamma}-ray peak identification is usually difficult due to the short measurement time that results in a lower {\gamma}-ray energy produced by the decay. Consequently, the resulting significant scattering in the low-energy side leads to strong statistical fluctuations and low detection efficiency that overwhelm the {\gamma}-ray peak. Here, we propose the use of shift invariance wavelet algorithm for low-energy part of the spectrum for weak {\gamma}-ray peak smoothing. The proposed algorithm not only overcomes the pseudo-Gibbs in the high-resolution {\gamma}-ray spectrum de-noising by the traditional wavelet transform, but also keeps quality of the weak {\gamma}-ray characteristic peak as well. Our new approach shows a significantly improved performance of the figure of merit (FOM) together with lower limit of quantitation (LLOQ) compared with the traditional wavelet transform. These results indicate the significant potential of our approach that could effectively increase the accuracy of weak {\gamma}-ray detecting activation analysis in TGS. 
Zhang Jinzha, Tuo Xianguo
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