Algorithms For Adaptive Histogram Equalization

Stephen M. Pizer; John D. Austin; Robert Cromartie; Ari Geselowitz; Bart ter Haar Romeny; John B. Zimmerman; Karel Zuiderveld

doi:10.1117/12.966688

1 January 1986 Algorithms For Adaptive Histogram Equalization

Stephen M. Pizer, John D. Austin, Robert Cromartie, Ari Geselowitz, Bart ter Haar Romeny, John B. Zimmerman, Karel Zuiderveld

Author Affiliations +

Proceedings Volume 0671, Physics and Engineering of Computerized Multidimensional Imaging and Processing; (1986) https://doi.org/10.1117/12.966688
Event: Physics and Engineering of Computerized Multidimensional Imaging and Processing, 1986, Newport Beach, CA, United States

Abstract

Adaptive histogram equalization (ahe) is a contrast enhancement method designed to be broadly applicable and having demonstrated effectiveness [Zimmerman, 1985]. 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.

Citation Download Citation

Stephen M. Pizer, John D. Austin, Robert Cromartie, Ari Geselowitz, Bart ter Haar Romeny, John B. Zimmerman, and Karel Zuiderveld "Algorithms For Adaptive Histogram Equalization", Proc. SPIE 0671, Physics and Engineering of Computerized Multidimensional Imaging and Processing, (1 January 1986); https://doi.org/10.1117/12.966688

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