Adaptive histogram equalization and its variations

S.M. Pizer, E.P. Amburn, J.D. Austin, R. Cromartie, A. Geselowitz, Trey Greer, B.M. Haar Romenij, ter, J.B. Zimmerman, K.J. Zuiderveld

    Research output: Contribution to journalArticleAcademicpeer-review

    1826 Citations (Scopus)
    18 Downloads (Pure)

    Abstract

    Adaptive histogram equalization (ahe) is a contrast enhancement method designed to be broadly applicable and having demonstrated effectiveness. However, slow speed and the overenhancement of noise it produces in relatively homogeneous regions are two problems. We report algorithms designed to overcome these and other concerns. We conclude that clipped ahe should become a method of choice in medical imaging and probably also in other areas of digital imaging, and that clipped ahe can be made adequately fast to be routinely applied in the normal display sequence.
    Original languageEnglish
    Pages (from-to)355-368
    Number of pages14
    JournalComputer Vision, Graphics, and Image Processing
    Volume39
    Issue number3
    DOIs
    Publication statusPublished - 1987

    Fingerprint

    Dive into the research topics of 'Adaptive histogram equalization and its variations'. Together they form a unique fingerprint.

    Cite this