The purpose of this book is to provide a practical introduction to the th- ries, techniques and applications of image fusion. The present work has been designed as a textbook for a one-semester ?nal-year undergraduate, or ?r- year graduate, course in image fusion. It should also be useful to practising engineers who wish to learn the concepts of image fusion and apply them to practical applications. In addition, the book may also be used as a supp- mentary text for a graduate course on topics in advanced image processing. The book complements the authoras previous work on multi-sensor data  fusion by concentrating exclusively on the theories, techniques and app- cations of image fusion. The book is intended to be self-contained in so far as the subject of image fusion is concerned, although some prior exposure to the ?eld of computer vision and image processing may be helpful to the reader. Apart from two preliminary chapters, the book is divided into three parts.In this case, we often impose the following additional requirements on the image fusion algorithms: Temporal stability. ... multi-resolution analysis, ensemble learning, bagging, boosting, color spaces, Markov random fields, image similarity measures and the expectation-maximization algorithm. ... The following matlab routines and toolboxes are of general utility and are widely used in image fusion.
|Publisher||:||Springer Science & Business Media - 2010-03-16|