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. This book offers an overview of the general principles and specifics 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).
1. Definitions, Isabelle Bloch, Henri Maître.
2. Fusion in Signal Processing, Jean-Pierre Le Cadre, Vincent Nimier and Roger Reynaud.
3. Fusion in Image Processing, Isabelle Bloch, Henri Maître.
4. Fusion in Robotics, Michèle Rombaut.
5. Information and Knowledge Representation in Fusion Problems, Isabelle Bloch, Henri Maître.
6. Probabilistic and Statistical Methods, Isabelle Bloch, Jean-Pierre Le Cadre and Henri Maître.
7. Belief Function Theory, Isabelle Bloch.
8. Fuzzy Sets and Possibility Theory, Isabelle Bloch.
9. Spatial Information in Fusion Methods, Isabelle Bloch.
10. Multi-agent Methods, Fabienne Ealet, Bertrand Collin and Catherine Garbay.
11. Fusion of Non-simultaneous Elements of Information: Temporal Fusion, Michèle Rombaut.
12. Conclusion, Isabelle Bloch.
Isabelle Bloch is Professor at the Ecole Nationale Supérieure des Télécommunications, Paris, France.