Table of Contents


Isabelle BLOCH

Chapter 1. Definitions

Isabelle BLOCH and Henri MAÎTRE

1.1. Introduction

1.2. Choosing a definition

1.3. General characteristics of the data

1.4. Numerical/symbolic

1.4.1. Data and information

1.4.2. Processes

1.4.3. Representations

1.5. Fusion systems

1.6. Fusion in signal and image processing and fusion in other fields

1.7. Bibliography

Chapter 2. Fusion in Signal Processing

Jean-Pierre LE CADRE, Vincent NIMIER and Roger REYNAUD

2.1. Introduction

2.2. Objectives of fusion in signal processing

2.2.1. Estimation and calculation of a law a posteriori

2.2.2. Discriminating between several hypotheses and identifying

2.2.3. Controlling and supervising a data fusion chain

2.3. Problems and specificities of fusion in signal processing

2.3.1. Dynamic control

2.3.2. Quality of the information

2.3.3. Representativeness and accuracy of learning and a priori information

2.4. Bibliography

Chapter 3. Fusion in Image Processing

Isabelle BLOCH and Henri MAÎTRE

3.1. Objectives of fusion in image processing

3.2. Fusion situations

3.3. Data characteristics in image fusion

3.4. Constraints

3.5. Numerical and symbolic aspects in image fusion

3.6. Bibliography

Chapter 4. Fusion in Robotics


4.1. The necessity for fusion in robotics

4.2. Specific features of fusion in robotics

4.2.1. Constraints on the perception system

4.2.2. Proprioceptive and exteroceptive sensors

4.2.3. Interaction with the operator and symbolic interpretation

4.2.4. Time constraints ...

Get Information Fusion in Signal and Image Processing: Major Probabilistic and Non-Probabilistic Numerical Approaches now with the O’Reilly learning platform.

O’Reilly members experience live online training, plus books, videos, and digital content from nearly 200 publishers.