Advanced techniques for fusion of information in Remote Sensing: An overview

M. Petrou, A. Stassopoulou

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

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 fulfilment 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 inference 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.

Original languageEnglish
Pages (from-to)264-275
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume3871
Publication statusPublished - 1999

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