• DocumentCode
    245526
  • Title

    Accelerating multi-scale retinex using ARM NEON

  • Author

    Ching-Tang Fan ; Jian-Ru Chen ; Chung-Wei Liang ; Yuan-Kai Wang

  • fYear
    2014
  • fDate
    26-28 May 2014
  • Firstpage
    77
  • Lastpage
    78
  • Abstract
    High dynamic range image processing have recently become an important topic in consumer electronics market. While multi-scale retinex with color restoration (MSRCR) have been well developed, disadvantages of low performance is not favorable to a mobile computer-vision system. To remedy the above problem, this paper proposes an accelerated MSRCR with effective use of ARM Cortex-A9 architecture and NEON SIMD technology. A linear sampling method with binomial normal approximation is developed for improving performance of Gaussian smoothing. Overall performance improvement of MSRCR algorithm on Zedboard platform is 74% compared to original ARM optimized C code compiled to Cortex-A9 processor architecture.
  • Keywords
    Gaussian processes; approximation theory; image colour analysis; image restoration; image sampling; microprocessor chips; smoothing methods; ARM Cortex-A9 processor architecture; ARM NEON; ARM optimized C code; Gaussian smoothing; MSRCR algorithm; NEON SIMD technology; Zedboard platform; binomial normal approximation; color restoration; consumer electronics market; high dynamic range image processing; linear sampling method; multiscale retinex acceleration; Acceleration; Approximation methods; Computer architecture; Image color analysis; Kernel; Lighting; Smoothing methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Consumer Electronics - Taiwan (ICCE-TW), 2014 IEEE International Conference on
  • Conference_Location
    Taipei
  • Type

    conf

  • DOI
    10.1109/ICCE-TW.2014.6904110
  • Filename
    6904110