Algorithms for adaptive histogram equalization

S.M. Pizer, J.D. Austin, R. Cromartie, A. Geselowitz, B.M. Haar Romenij, ter, J.B. Zimmerman, K.J. Zuiderveld

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    6 Citations (Scopus)
    8 Downloads (Pure)


    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 summarize algorithms designed to overcome these and other concerns. These algorithms include interpolated ahe, to speed up the method on general purpose computers; a version of interpolated ahe designed to run in a few seconds on feedback processors; a version of full ahe designed to run in under one second on custom VLSI hardware; and clipped ahe, designed to overcome the problem of overenhancement of noise contrast. 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
    Title of host publicationPhysics and Engineering of Computerized Multidimensional Imaging and Processing, Newport Beach, United States, April 2, 1988
    EditorsT.F. Budinger, Z.-H. Cho, O. Nalcioglu
    Place of PublicationBellingham
    Publication statusPublished - 1986

    Publication series

    NameProceedings of SPIE
    ISSN (Print)0277-786X


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