Identification of radionuclides present in trace amount in a high resolution gamma spectrum using wavelet transformation based denoising

For fast and non-destructive qualitative and quantitative estimate of routinely released gamma emitting radionuclides from nuclear facilities, Gamma Spectrometry is carried out. Presence of instrumental, statistical noise and Compton continuum contributions from the higher energy radionuclides proper estimation of activity becomes difficult. So filtering of the spectrum is very important for identification and evaluation of area under the gamma peak. In this work, method based on wavelet transformation (WT) is implemented for denoising of high resolution gamma spectrum obtained from plant leaves samples using an HPGe detector. Work describes the details of the WT and its application for filtering the noise in a gamma spectrum and identification of 208Tl, 137Cs, 60Co, 40K present in trace amount with an enhanced signal to noise ratio (SNR). For low activity environmental sample (plant leaves), WT based methodology provide significant improvement in SNR (about twofold). With WT methodology, the presence of 60Co (1173 and 1332 keV) and 208Tl (2612 keV) were detected with 99.7% confidence, which were not detected in the original spectrum