Introduction

Abstract

The subject of this book is image fusion which we define as the process of combining multiple input images into a single composite image. Our aim is to create from the collection of input images a single output image which contains a better description of the scene than the one provided by any of the individual input images. The output image should therefore be more useful for human visual perception or for machine perception. The basic problem of image fusion is one of determining the best procedure for combining the multiple input images. The view adopted in this book is that combining multiple images with a priori information is best handled within a statistical framework. In particular we shall restrict ourselves to classical and robust statistical approaches, Bayesian methods, sub-space and wavelet techniques.