• DocumentCode
    248142
  • Title

    Sparse image recovery using compressed sensing over finite alphabets

  • Author

    Bioglio, Valerio ; Coluccia, Giulio ; Magli, Enrico

  • Author_Institution
    Dipt. di Elettron. e Telecomun., Politec. di Torino, Turin, Italy
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    1287
  • Lastpage
    1291
  • Abstract
    In this paper we present F2 OMP, a recovery algorithm for Compressed Sensing over finite fields. Classical recovery algorithms do not exploit the fact that a signal may belong to a finite alphabet, while we show that this information can lead to more efficient reconstruction algorithms. As an application, we use the proposed algorithm to recover sparse grayscale images, showing that performing CS operation over a finite field can outperform classical recovery algorithms from visual quality, memory occupation and complexity point of view.
  • Keywords
    compressed sensing; image reconstruction; CS operation; F2OMP; compressed sensing; finite alphabets; memory occupation; reconstruction algorithms; recovery algorithms; sparse grayscale images; sparse image recovery; visual quality; Compressed sensing; Image reconstruction; Loss measurement; Matching pursuit algorithms; Sensors; Sparse matrices; Vectors; Compressed Sensing; Finite Fields; Orthogonal Matching Pursuit; Sparse Image Recovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025257
  • Filename
    7025257