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Proceedings Paper

Cross-sensor fusion of imagery for improved information extraction
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Paper Abstract

We combined cross-sensor data that leads to improved extraction of information from disparate sensors. We presented a new method for signal fusion that uses different transforms for the forward transforms of two images and a common transform for the inverse. When using a fusion rule that selects the maximum value between images, we were able to transfer more energy to the result using our method. Our method could form the basis of a new image fusion approach because it offers a way to transfer more energy to the result not possible with a conventional approach.

Paper Details

Date Published: 17 April 2006
PDF: 7 pages
Proc. SPIE 6247, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV, 624707 (17 April 2006); doi: 10.1117/12.666460
Show Author Affiliations
S. P. Kozaitis, Florida Institute of Technology (United States)
M. Ouendeno, Florida Institute of Technology (United States)


Published in SPIE Proceedings Vol. 6247:
Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV
Harold H. Szu, Editor(s)

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