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Proceedings Paper

Algorithms For Adaptive Histogram Equalization
Author(s): Stephen M. Pizer; John D. Austin; Robert Cromartie; Ari Geselowitz; Bart ter Haar Romeny; John B. Zimmerman; Karel Zuiderveld
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Paper 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.

Paper Details

Date Published: 1 January 1986
PDF: 7 pages
Proc. SPIE 0671, Physics and Engineering of Computerized Multidimensional Imaging and Processing, (1 January 1986); doi: 10.1117/12.966688
Show Author Affiliations
Stephen M. Pizer, University of North Carolina (United States)
John D. Austin, University of North Carolina (United States)
Robert Cromartie, University of North Carolina (United States)
Ari Geselowitz, Pennsylvania State University (United States)
Bart ter Haar Romeny, Academisch Ziekenhuis Utrecht (Netherlands)
John B. Zimmerman, Washington University (United States)
Karel Zuiderveld, Academisch Ziekenhuis Utrecht (Netherlands)

Published in SPIE Proceedings Vol. 0671:
Physics and Engineering of Computerized Multidimensional Imaging and Processing
Thomas F. Budinger; Zang-Hee Cho; Orhan Nalcioglu, Editor(s)

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