• DocumentCode
    77554
  • Title

    Pileup Correction Algorithm using an Iterated Sparse Reconstruction Method

  • Author

    Trigano, Tom ; Gildin, Ilia ; Sepulcre, Yann

  • Author_Institution
    Dept. of Electr. & Electron. Eng., SCE, Ashdod, Israel
  • Volume
    22
  • Issue
    9
  • fYear
    2015
  • fDate
    Sept. 2015
  • Firstpage
    1392
  • Lastpage
    1395
  • Abstract
    Every radioactive source can be characterized by an histogram obtained after collecting the energies of photons emitted from the source, also called energy spectrum. However, when the activity of this source is high, a physical phenomenon known as the pile-up effect distorts direct measurements, resulting in a significant distortion of the energy spectrum. We suggest in this letter an iterative algorithm to attenuate the pile-up effect and enhance the resulting energy spectra. It is based on iterations of a post-processed, non-negative, version of the Least Absolute Shrinkage and Selection Operator (LASSO). Results on simulations and real data illustrate the improvement obtained by the proposed method.
  • Keywords
    compressed sensing; gamma-ray spectrometers; iterative methods; radioactive sources; LASSO; Least Absolute Shrinkage-and-Selection Operator; compressive sensing; energy spectrum; gamma spectrometer; histogram; iterated sparse reconstruction method; iterative algorithm; physical phenomenon; pile-up effect; pileup correction algorithm; radioactive source; Computational modeling; Distortion measurement; Estimation; Histograms; Photonics; Shape; Signal processing algorithms; Compressive sensing; nuclear spectroscopy; signal restoration and enhancement; sparse reconstruction;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2015.2406911
  • Filename
    7047735