• DocumentCode
    879435
  • Title

    Recursively separated and weighted histogram equalization for brightness preservation and contrast enhancement

  • Author

    Kim, Mary ; Chung, Min Gyo

  • Author_Institution
    Dept. of Comput. Sci., Seoul Women´´s Univ., Seoul
  • Volume
    54
  • Issue
    3
  • fYear
    2008
  • fDate
    8/1/2008 12:00:00 AM
  • Firstpage
    1389
  • Lastpage
    1397
  • Abstract
    This paper proposes a new histogram equalization method, called RSWHE (recursively separated and weighted histogram equalization), for brightness preservation and image contrast enhancement. The essential idea of RSWHE is to segment an input histogram into two or more sub-histograms recursively, to modify the sub-histograms by means of a weighting process based on a normalized power law function, and to perform histogram equalization on the weighted sub-histograms independently. RSIHE (recursive sub-image histogram equalization) and RMSHE (recursive mean separate histogram equalization) are some methods similar to RSWHE, but they do not carry out the above weighting process. We show that compared to other existent methods, RSWHE preserves the image brightness more accurately and produces images with better contrast enhancement.
  • Keywords
    equalisers; image enhancement; image segmentation; recursive estimation; brightness preservation; image contrast enhancement; normalized power law function; recursive mean separate histogram equalization; recursive sub-image histogram equalization; recursively separated and weighted histogram equalization; Brightness; Computer errors; Computer science; Consumer electronics; Distribution functions; Dynamic range; Helium; Histograms; Image converters; Image segmentation; Histogram equalization, contrast enhancement, brightness preservation, histogram weighting;
  • fLanguage
    English
  • Journal_Title
    Consumer Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0098-3063
  • Type

    jour

  • DOI
    10.1109/TCE.2008.4637632
  • Filename
    4637632