• DocumentCode
    1680858
  • Title

    Analysis-by-synthesis-based quantization of compressed sensing measurements

  • Author

    Shirazinia, Amirpasha ; Chatterjee, Saptarshi ; Skoglund, Mikael

  • Author_Institution
    Commun. Theor. Lab., ACCESS Linnaeus Centre, Stockholm, Sweden
  • fYear
    2013
  • Firstpage
    5810
  • Lastpage
    5814
  • Abstract
    We consider a resource-constrained scenario where a compressed sensing- (CS) based sensor has a low number of measurements which are quantized at a low rate followed by transmission or storage. Applying this scenario, we develop a new quantizer design which aims to attain a high-quality reconstruction performance of a sparse source signal based on analysis-by-synthesis framework. Through simulations, we compare the performance of the proposed quantization algorithm vis-a-vis existing quantization methods.
  • Keywords
    compressed sensing; mean square error methods; quantisation (signal); signal reconstruction; signal sources; analysis by synthesis based quantization; compressed sensing measurements; high quality reconstruction performance; quantization methods; quantizer design; resource constrained scenario; sparse source signal; Algorithm design and analysis; Compressed sensing; Distortion measurement; Encoding; Indexes; Quantization (signal); Vectors; Quantization; analysis-bysynthesis; compressed sensing; mean-square error; sparsity;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
  • Conference_Location
    Vancouver, BC
  • ISSN
    1520-6149
  • Type

    conf

  • DOI
    10.1109/ICASSP.2013.6638778
  • Filename
    6638778