Image registration is a digital processing discipline that studies how to bring two or more digital images into precise alignment for analysis and comparison. Accurate registration algorithms are essential for creating mosaics of satellite images and tracking changes on the planet's surface over time. Bringing together invited contributions from 36 distinguished researchers, Image Registration for Remote Sensing presents a detailed overview of current research and practice in the application of image registration to remote sensing imagery. Chapters cover the problem definition, theoretical issues in accuracy and efficiency, fundamental algorithms, and real-world case studies of image registration software applied to imagery from operational satellite systems. Image Registration for Remote Sensing provides a comprehensive and practical overview for Earth and space scientists, presents image processing researchers with a summary of current research, and can be used for specialised graduate courses.
Foreword Jon A. Benediktsson
Part I. The Importance of Image Registration for Remote Sensing:
1. Introduction Jacqueline Le Moigne, Nathan S. Netanyahu and Roger D. Eastman
2. Influence of image registration on validation efforts Bin Tan and Curtis E. Woodcock
3. Survey of image registration methods Roger D. Eastman, Nathan S. Netanyahu and Jacqueline Le Moigne
Part II. Similarity Metrics for Image Registration:
4. Fast correlation and phase correlation Harold S. Stone
5. Matched filtering techniques Qin-Sheng Chen
6. Image registration using mutual information Arlene A. Cole-Rhodes and Pramod K. Varshney
Part III. Feature Matching and Strategies for Image Registration:
7. Registration of multiview images A. Ardeshir Goshtasby
8. New approaches to robust, point-based image registration David M. Mount, Nathan S. Netanyahu and San Ratanasanya
9. Condition theory for image registration and post-registration error estimation Charles S. Kenney, B. S. Manjunath, Marco Zuliani and Kaushal Solanki
10. Feature-based image to image registration Venu M. Govindu and Rama Chellappa
11. On the use of wavelets for image registration Jacqueline Le Moigne, Ilya Zavorin and Harold S. Stone
12. Gradient descent approaches to image registration Arlene A. Cole-Rhodes and Roger D. Eastman
13. Bounding the performance of image registration Min Xu and Parmod K. Varshney
Part IV. Applications and Operational Systems:
14. Multi-temporal and multi-sensor image registration Jacqueline Le Moigne, Arlene A. Cole-Rhodes, Roger D. Eastman, Nathan S. Netanyahu, Harold S. Stone, Ilya Zavorin and Jeffrey T. Morisette
15. Georegistration of meteorological images James L. Carr
16. Challenges, solutions, and applications of accurate multi-angle image registration: lessons learned from MISR Veljko M. Jovanovic, David J. Diner and Roger Davies
17. Automated AVHRR image navigation William J. Emery, R. Ian Crocker and Daniel G. Baldwin
18. Landsat image geocorrection and registration James C. Storey
19. Automatic and precise orthorectification of SPOT images Simon Baillarin, Aurélie Bouillon and Marc Bernard
20. Geometry of the VEGETATION sensor Sylvia Sylvander
21. Accurate MODIS global geolocation through automated ground control image matching Robert E. Wolfe and Masahiro Nishihama
22. SeaWIFS operational geolocation assessment system Frederick S. Patt
Part V. Conclusion:
23. Concluding remarks Jacqueline Le Moigne, Nathan S. Netanyahu and Roger D. Eastman
Jacqueline Le Moigne is the Assistant Chief for Technology in the Software Engineering Division at NASA-Goddard Space Flight Center where she leads the strategic vision and the development of technology goals and objectives. During her 20 years experience at NASA, Dr Le Moigne has performed significant work in the processing and the analysis of remote sensing data. She has become an international expert in image registration, especially as it relates to the use of wavelet analysis, high-performance and on-board processing. She has been an Associate Editor for the IEEE Transactions on Geoscience and Remote Sensing and for the journal Pattern Recognition.
Nathan S. Netanyahu is an Associate Professor in the Department of Computer Science at Bar-Ilan University, Israel, and is also affiliated with the Brain Research Center at Bar-Ilan University and the Center for Automation Research at the University of Maryland, College Park. He has previously worked for the Israeli Ministry of Defense, the Space Data and Computing Division, NASA-Goddard Space Flight Center, and for the Center for Excellence in Space Data and Information Sciences (CESDIS) at NASA-Goddard. Professor Netanyahu's main research interests are in the areas of algorithm design and analysis, computational geometry, image processing, pattern recognition, remote sensing, and robust statistical estimation.
Roger D. Eastman is an Associate Professor of Computer Science at Loyola University Maryland, with over 25 years of experience in image matching and registration for medical, robotic and Earth science applications. Professor Eastman has collaborated with NASA-Goddard researchers in Earth science registration on techniques for generalizing and evaluating algorithms, and for robust sub-pixel registration, and with NIST-Gaithersburg researchers on advanced sensors for manufacturing robotics for general assembly. He regularly reviews articles on image registration for the IEEE Transactions on Geoscience and Remote Sensing and other remote sensing venues.
"The book explains the main image-registration issues involved in remote sensing in a comprehensive, convincing, and well-written manner. The coverage of the topic is excellent, and experimental examples with simulated and real data are also shown in most chapters. The reading is accessible to both specialists and nonspecialists, including students. Stimulating discussions on scientific and applicative challenges, possible solution strategies, and the accuracy, optimality, and efficiency of such strategies can be found throughout the book and make it an outstanding treatise that can be extremely interesting to a wide audience."
– IEEE Geoscience and Remote Sensing Society Newsletter
"This is an important reference book for all remote-sensing professionals as well as for advanced level geophysical data processing personnel in academia and in industry."
– Wooil M. Moon, The Leading Edge