17 November 1995 Active fusion for remote sensing image understanding
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Abstract
Remote sensing applications are often characterized by a high degree of complexity. The large amount of data to be processed and the high degree of uncertainty inherent in this processing make it necessary to actively select the most useful information. We introduce a general framework, called `active fusion', that actively selects and combines information from multiple sources in order to arrive at a reliable result at reasonable costs. An outline is given of how to implement such a framework using Bayesian networks and decision theoretical techniques. Finally, we develop a number of future scenarios where such an active fusion component might be useful for remote sensing applications.
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Axel J. Pinz, Axel J. Pinz, Manfred Prantl, Manfred Prantl, } "Active fusion for remote sensing image understanding", Proc. SPIE 2579, Image and Signal Processing for Remote Sensing II, (17 November 1995); doi: 10.1117/12.226863; https://doi.org/10.1117/12.226863
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