Architecture and design of a diagnostic information fusion system
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Information combination operators for data fusion: a comparative review with classification
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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To acquire detection performance required for an operational system in the detection for satellite image for environmental changes, it is necessary to use multiple images over years to know the environmental changes over years. This paper describes a method for decision-level fusion technique where the fusion can compensate for correlation among images. The fusion is done using possibilistic combiners based on T-norms families that better represent the correlation of images. This technique was applied to satellite images for free vegetation of Africa (1998 April 01, 1998 September 01). The performance of this technique, compared to the other techniques such as naïve Bayes, Dempster-Shafer, voting, rule-based and linear discriminant, is evaluated by simple theoretical models.