Optical EngineeringImage fusion of synthetic aperture radar and optical data for terrain classification with a variance reduction technique
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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.