Data Fusion Definitions and Architectures

ISBN9782911762383 EditeurPresses MINES ParisTech pages200 Parution2002-02-01
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Argumentaire

Data fusion is a formal framework in which are expressed the means and tools for the alliance of data originating from different sources. It means an approach to information extraction spontaneously adopted in several domains before this was expressed as "data fusion". This approach is based upon the synergy offered by the various sources. Applications are numerous, from biology to civil aviation.

This book clearly establishes the fundamentals (particularly definitions and architectures) in data fusion. It can be read with profit by anyone interested in data fusion, whatever his domain of expertise, and should be valuable to engineers, scientists and practitioners.

The second part of the book is devoted to methods for the fusion of images. It offers an in-depth presentation of standard and advanced methods for the fusion of multi-modality images. The emphasis is put on images having different spatial resolutions, but the book is not limited to this case. Given several sets of images acquired by disparate sensors, the problems treated are to create new sets of images of reduced dimensionality, in order to either better visualize the original sets of images as a comprehensive ensemble of information, or to synthesize images with a better spatial resolution.
AUTHOR
L. Wald graduated in Theoretical Physics (France-1977). After his PhD (Paris-1980) on the applications of remote sensing to oceanography, he obtained his Doctorat d'Etat ès Sciences (1985). Since 1991, he is a Professor at Ecole des Mines de Paris, where he is currently the Head of the Remote Sensing Group, and is focusing his own research in applied mathematics, meteorology and oceanography. He obtained the Autometrics Award (1998) and the Erdas Award (2001) for articles on data fusion. His career in information technologies has been rewarded in 1996 by the famous French Blondel Medal.