• DocumentCode
    862877
  • Title

    Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation

  • Author

    Chen, Soong-Der ; Ramli, Abd Rahman

  • Author_Institution
    Putra Malaysia Univ., Serdang, Malaysia
  • Volume
    49
  • Issue
    4
  • fYear
    2003
  • Firstpage
    1301
  • Lastpage
    1309
  • Abstract
    Histogram equalization (HE) is widely used for contrast enhancement. However, it tends to change the brightness of an image and hence, not suitable for consumer electronic products, where preserving the original brightness is essential to avoid annoying artifacts. Bi-histogram equalization (BBHE) has been proposed and analyzed mathematically that it can preserve the original brightness to a certain extend. However, there are still cases that are not handled well by BBHE, as they require higher degree of preservation. This paper proposes a generalization of BBHE referred to as recursive mean-separate histogram equalization (RMSHE) to provide not only better but also scalable brightness preservation. BBHE separates the input image´s histogram into two based on its mean before equalizing them independently. While the separation is done only once in BBHE, this paper proposes to perform the separation recursively; separate each new histogram further based on their respective mean. It is analyzed mathematically that the output image´s mean brightness will converge to the input image´s mean brightness as the number of recursive mean separation increases. Besides, the recursive nature of RMSHE also allows scalable brightness preservation, which is very useful in consumer electronics. Simulation results show that the cases which are not handled well by HE, BBHE and dualistic sub image histogram equalization (DSIHE), have been properly enhanced by RMSHE.
  • Keywords
    brightness; image enhancement; bihistogram equalization; contrast enhancement; digital image; dualistic sub image histogram equalization; mathematical analysis; recursive mean-separate; recursive mean-separate histogram equalization; scalable brightness preservation; Biomedical image processing; Brightness; Consumer electronics; Dynamic range; Entropy; Helium; Histograms; Image analysis; Image converters; Probability distribution;
  • fLanguage
    English
  • Journal_Title
    Consumer Electronics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0098-3063
  • Type

    jour

  • DOI
    10.1109/TCE.2003.1261233
  • Filename
    1261233