Image Registration for Remote Sensing

Image registration employs digital image processing in order 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 thirty-six distinguished researchers, the book 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. This book 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; Glossary; Index.

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 twenty 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 twenty-five 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