Pile-Up Correction in Spectroscopic Signals Using Regularized Sparse Reconstruction

Abstract

Pile-up is a common problem in high-count-rate gamma spectroscopy. Many techniques have been introduced to overcome this problem. Sparse reconstruction is a recent signal processing method that could be used to solve this problem. In this article, we propose a modified sparse reconstruction method to overcome pulse pile-up, especially with ultrahigh count rates. The method uses two regularization terms to compensate for the error caused by an inadequate sampling rate that is called the “verbosity” problem. It significantly improves the pile-up correction process. A scintillation detector pulse train is simulated in different rates by a Monte Carlo approach. Then, the proposed method is validated, and good results are achieved in ultrahigh count rates.