
Image Fusion
Theories, Techniques and Applications
H.B. Mitchell(Author)
Springer (Publisher)
Published on 29. November 2014
Book
Paperback/Softback
XVI, 247 pages
978-3-642-42503-5 (ISBN)
Description
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 author's previous work on multi-sensor data [1] 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.
More details
Edition
2010 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
XVI, 247 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 15 mm
Weight
406 gr
ISBN-13
978-3-642-42503-5 (9783642425035)
DOI
10.1007/978-3-642-11216-4
Schweitzer Classification
Other editions
Additional editions

Book
02/2010
Springer
€106.99
Shipment within 7-9 days
Content
Image Sensors.- I: Theories.- Common Representational Format.- Spatial Alignment.- Semantic Equivalence.- Radiometric Calibration.- Pixel Fusion.- II: Techniques.- Multi-resolution Analysis.- Image Sub-space Techniques.- Ensemble Learning.- Re-sampling Methods.- Image Thresholding.- Image Key Points.- Image Similarity Measures.- Vignetting, White Balancing and Automatic Gain Control Effects.- Color Image Spaces.- Markov Random Fields.- Image Quality.- III: Applications.- Pan-sharpening.- Ensemble Color Image Segmentation.- STAPLE: Simultaneous Truth and Performance Level Estimation.- Biometric Technologies.