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Optical Engineering

Image fusion of synthetic aperture radar and optical data for terrain classification with a variance reduction technique
Author(s): Yu-Chang Tzeng; Kun-Shan Chen
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Paper Abstract

The multiple-classifiers approach is utilized to fully take into account the complementary and supplementary information from different data sources for terrain cover classification. To combine the outputs of classifiers that may be conditionally dependent, a variance reduction technique was adopted for optimal voting and thus best information extraction. The effectiveness and efficiency of utilizing the variance-reduction technique was demonstrated using SAR and optical images. Results show that the classification accuracy is dramatically improved by the proposed method.

Paper Details

PDF: 8 pages
Opt. Eng. 44(10) 106202 doi: 10.1117/1.2113107
Published in: Optical Engineering Volume 44, Issue 10, October 2005
Show Author Affiliations
Yu-Chang Tzeng, National United Univ. (Taiwan)
Kun-Shan Chen, National Central Univ. (Taiwan)


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