Information Fusion In Signal And Image Processing

The area of information fusion has grown considerably during the last few years, leading to a rapid and impressive evolution. In such fast-moving times, it is important to take stock of the changes that have occurred. As such, this books offers an overview of the general principles and specificities of information fusion in signal and image processing, as well as covering the main numerical methods (probabilistic approaches, fuzzy sets and possibility theory and belief functions).

Isabelle Bloch is Professor at the Ecole Nationale Supérieure des
Télécommunications, Paris, France.

Chapter 1. Definitions (Isabelle Bloch, Henri Maître).
Chapter 2. Fusion in signal processing (Jean-Pierre Le Cadre, Vincent Nimier and Roger Reynaud).
Chapter 3. Fusion in image processing (Isabelle Bloch, Henri Maître).
Chapter 4. Fusion in robotics (Michèle Rombaut).
Chapter 5. Information and knowledge representation in fusion problems (Isabelle Bloch, Henri Maître).
Chapter 6. Probabilistic and statistical approaches (Isabelle Bloch, Jean-Pierre Le Cadre and Henri Maître).
Chapter 7. Belief function theory (Isabelle Bloch).
Chapter 8. Fuzzy sets and possibility theory (Isabelle Bloch).
Chapter 9. Spatial information in fusion methods (Isabelle Bloch).
Chapter 10. Multi-agent methods (Fabienne Ealet, Bertrand Collin and Catherine Garbay).
Chapter 11. Fusion of non-simultaneous elements of information, temporal fusion (Michèle Rombaut).
Chapter 12. Conclusion (Isabelle Bloch).
List of Authors.
Index.