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Proceedings Paper

Advanced techniques for fusion of information in remote sensing: an overview
Author(s): Maria Petrou; A. Stassopoulou
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Paper Abstract

Traditional techniques for fusing information in Remote Sensing and related disciplines rely on the application of expert rules. These rules, are often applied to data held in the layers of a GIS which are spatially superimposed to yield conclusions based on the fulfillment of certain conditions. Modern techniques in fusion of information try to take into consideration the uncertainty of each source of information. They are divided in distributed and centralized systems according to whether conclusions reached by different classifiers relying on different sources of information are combined, or all data from all available sources of information are used together by a single reference mechanism. In terms of the central inference mechanism used, these techniques fall in six categories, namely rule-based, fuzzy systems, Dempster-Shafer systems, Pearl's inference networks, other probabilistic approaches, and neural networks. All these approaches are discussed and compared.

Paper Details

Date Published: 14 December 1999
PDF: 12 pages
Proc. SPIE 3871, Image and Signal Processing for Remote Sensing V, (14 December 1999); doi: 10.1117/12.373264
Show Author Affiliations
Maria Petrou, Univ. of Surrey (United Kingdom)
A. Stassopoulou, Univ. of Surrey (United Kingdom)

Published in SPIE Proceedings Vol. 3871:
Image and Signal Processing for Remote Sensing V
Sebastiano Bruno Serpico, Editor(s)

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