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14 December 1999 Advanced techniques for fusion of information in remote sensing: an overview
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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.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maria Petrou and A. Stassopoulou "Advanced techniques for fusion of information in remote sensing: an overview", Proc. SPIE 3871, Image and Signal Processing for Remote Sensing V, (14 December 1999); https://doi.org/10.1117/12.373264
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