Information Fusion in Signal and Image Processing: Major Probabilistic and Non-Probabilistic Numerical Approaches

Chapter 1

Definitions

1.1. Introduction

Fusion has become an important aspect of information processing in several very different fields, in which the information that needs to be fused, the objectives, the methods, and hence the terminology, can vary greatly, even if there are also many analogies. The objective of this chapter is to specify the context of fusion in the field of signal and image processing, to specify the concepts and to draw definitions. This chapter should be seen as a guide for the entire book. It should help those with another vision of the problem to find their way.

1.2. Choosing a definition

In this book, the word “information” is used in a broad sense. In particular, it covers both data (for example, measurements, images, signals, etc.) and knowledge (regarding the data, the subject, the constraints, etc.) that can be either generic or specific.

The definition of information fusion that we will be using throughout this book is given below.

DEFINITION 1.1 (Fusion of information). Fusion of information consists of combining information originating from several sources in order to improve decision making.

This definition, which is largely the result of discussions led within the GDR-PRC ISIS¹ workgroup on information fusion, is general enough to encompass the diversity of fusion problems encountered in signal and image processing. Its appeal lies in the fact that it focuses on the combination and decision phases, i.e. two operations that can take different ...