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

Abstract

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

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