Tor Vergata Earth Observation Laboratory

Decision fusion for the classification of
hyperspectral data: Outcome of the 2008 GRS-S
Data Fusion Contest

Giorgio Licciardi, Fabio Pacifici, Devis Tuia, Saurabh Prasad, Terrance West, Ferdinando Giacco, Christian Thiel, Jordi Inglada, Emmanuel Christophe, Jocelyn Chanussot, and Paolo Gamba



The 2008 Data Fusion Contest that was organized by the IEEE Geoscience and Remote Sensing Data Fusion Technical Committee was dealing with the classification of high resolution hyperspectral data from an urban area. Unlike in previous issues of the contest, the goal was not only to identify the best algorithm, but also to provide a collaborative effort: the decision fusion of the best individual algorithms was aiming at further improving the classification performances and the best algorithms were ranked according to their relative contribution to the decision fusion. This paper presents the five awarded algorithms and the conclusions of the contest, stressing the importance of decision fusion, of dimension reduction and of supervised classification methods, such as the Neural Networks and the Support Vector Machines.

Index Terms—decision fusion, classification, hyperspectral imagery

This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible.

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder


|| full paper || earth observation laboratory ||