Gamma Ray Spectrum Unfolding Using Derivative Kernels

The unfolding of a gamma ray spectrum experience many difficulties due to noise in the recorded data, that is based mainly on the change of photon energy due to scattering mechanisms (either in the detector or the medium), the accumulation of recorded counts in a fixed energy interval (the channel width of the detector) and finally the statistical fluctuation inside the detector. In order to deal with these problems, a new method is developed which interpolates the ideal spectrum with the use of special designed derivative kernels. Preliminary simulation results are presented and show that this approach is very effective even in spectra with low statistics.