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We demonstrate a new approach to efficiently detect weak {\gamma}-ray peak ofthe radioactive waste in tomographic {\gamma} scanning (TGS). In the TGSmeasurement, {\gamma}-ray peak identification is usually difficult due to theshort measurement time that results in a lower {\gamma}-ray energy produced bythe decay. Consequently, the resulting significant scattering in the low-energyside leads to strong statistical fluctuations and low detection efficiency thatoverwhelm the {\gamma}-ray peak. Here, we propose the use of shift invariancewavelet algorithm for low-energy part of the spectrum for weak {\gamma}-raypeak smoothing. The proposed algorithm not only overcomes the pseudo-Gibbs inthe high-resolution {\gamma}-ray spectrum de-noising by the traditional wavelettransform, but also keeps quality of the weak {\gamma}-ray characteristic peakas well. Our new approach shows a significantly improved performance of thefigure of merit (FOM) together with lower limit of quantitation (LLOQ) comparedwith the traditional wavelet transform. These results indicate the significantpotential of our approach that could effectively increase the accuracy of weak{\gamma}-ray detecting activation analysis in TGS.

A new approach in the detection of weak {\gamma}-ray peak of the radioactive waste in tomography {\gamma} scanning