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

Yu-Chang Tzeng; Kun-Shan Chen

doi:10.1117/1.2113107

1 October 2005 Image fusion of synthetic aperture radar and optical data for terrain classification with a variance reduction technique

Yu-Chang Tzeng, Kun-Shan Chen

Author Affiliations +

Optical Engineering, Vol. 44, Issue 10, 106202 (October 2005). https://doi.org/10.1117/1.2113107

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.

©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Yu-Chang Tzeng and Kun-Shan Chen "Image fusion of synthetic aperture radar and optical data for terrain classification with a variance reduction technique," Optical Engineering 44(10), 106202 (1 October 2005). https://doi.org/10.1117/1.2113107

Published: 1 October 2005

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