Semantic Map Generation from Satellite Images for Humanitarian Scenarios Applications

Authors:
Corina Vaduva;Daniela Faur;Anca Popescu;Inge Gavat;Mihai Datcu
Affiliations:
University POLITEHNICA Bucharest, Bucharest, Romania;University POLITEHNICA Bucharest, Bucharest, Romania;University POLITEHNICA Bucharest, Bucharest, Romania;University POLITEHNICA Bucharest, Bucharest, Romania;German Aerospace Center, DLR, Oberffafenhofen, Germany
Venue:
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Year:
2008

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Mutual information based measure for image content characterization

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IEEE Transactions on Information Theory

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Abstract

This paper demonstrates how knowledge driven methods and the associated data analysis algorithms are changing the paradigms of user-data interactions, providing an easier and wider access to the Earth Observation data. Some information theory based algorithms are proposed for anomaly and change detection on SPOT images, relative to a widespread humanitarian crisis scenario: floods. The outcomes of these algorithms define an informational representation of the image, revealing the spatial distribution of a particular theme. Using image analysis and interpretation, the multitude of features from a scene are classified into meaningful classes to create sematic maps.