• DocumentCode
    597880
  • Title

    Hierarchical recursive running median

  • Author

    Alekseychuk, A.

  • Author_Institution
    Comput. Vision & Remote Sensing, Tech. Univ. Berlin, Berlin, Germany
  • fYear
    2012
  • fDate
    Sept. 30 2012-Oct. 3 2012
  • Firstpage
    109
  • Lastpage
    112
  • Abstract
    Median filter was long known in image processing for its high computational costs. Recently, an algorithm was developed which is able to compute median on integer-valued images in a roughly constant average time. A new O(1) algorithm presented here further improves the aforementioned one, being at the time of writing the lowest theoretical complexity algorithm for calculation of 2D and higher dimensional median filters. The algorithm scales naturally to higher precision (e.g. 16-bit) integer data without any modifications. Its adaptive version offers additional speed-up for images showing compact modes in gray-value distribution. The algorithm will be useful for high bit depth data or on hardware without SIMD extensions. A C/C++ implementation is available under GPL for research purposes.
  • Keywords
    C++ language; computational complexity; image processing; median filters; C-C++ implementation; O(1) algorithm; SIMD extension; complexity algorithm; gray-value distribution; hierarchical recursive running median filter; image processing; integer-valued image; single instruction multiple data; Approximation algorithms; Computational complexity; Histograms; Runtime; Signal processing algorithms; Vegetation; computational complexity; computational efficiency; filtering algorithms; nonlinear filters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2012 19th IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4673-2534-9
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2012.6466807
  • Filename
    6466807