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Journal of Electronic Imaging

Fast algorithms for histogram matching: application to texture synthesis
Author(s): Jannick P. Rolland; V. Vo; B. Bloss; Craig K. Abbey
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Paper Abstract

Texture synthesis is the ability to create ensembles of images of similar structures from sample textures that have been photographed. The method we employ for texture synthesis is based on histogram matching of images at multiple scales and orientations. This paper reports two fast and in one case simple algorithms for histogram matching. We show that the sort-matching and the optimal cumulative distribution function (CDF)-matching (OCM) algorithms provide high computational speed compared to that provided by the conventional approach. The sort-matching algorithm also provides exact histogram matching. Results of texture synthesis using either method show no subjective perceptual differences. The sort-matching algorithm is attractive because of its simplicity and speed, however as the size of the image increases, the OCM algorithm may be preferred for optimal computational speed.

Paper Details

Date Published: 1 January 2000
PDF: 7 pages
J. Electron. Imaging. 9(1) doi: 10.1117/1.482725
Published in: Journal of Electronic Imaging Volume 9, Issue 1
Show Author Affiliations
Jannick P. Rolland, CREOL/Univ. of Central Florida (United States)
V. Vo, Univ. of Central Florida (United States)
B. Bloss, Univ. of Central Florida (United States)
Craig K. Abbey, Cedars-Sinai Medical Ctr. (United States)


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