DIGITAL IMAGING PROCESSING

Fast algorithms for histogram matching: Application to texture synthesis

[+] Author Affiliations
J. P. Rolland

University of Central Florida, School of Optics and CREOL, School of Electrical Engineering and Computer Science, Orlando, Florida?32816

V. Vo, B. Bloss

University of Central Florida, School of Electrical Engineering and Computer Science, Orlando, Florida?32816

C. K. Abbey

University of Arizona, Program in Applied Mathematics, Tucson, Arizona?85724

J. Electron. Imaging. 9(1), 39-45 (Jan 01, 2000). doi:10.1117/1.482725
History: Received Apr. 15, 1998; Revised May 11, 1999; Revised Oct. 29, 1999; Accepted Nov. 3, 1999
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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. © 2000 SPIE and IS&T.

© 2000 SPIE and IS&T

Topics

Algorithms

Citation

J. P. Rolland ; V. Vo ; B. Bloss and C. K. Abbey
"Fast algorithms for histogram matching: Application to texture synthesis", J. Electron. Imaging. 9(1), 39-45 (Jan 01, 2000). ; http://dx.doi.org/10.1117/1.482725


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