This book provides a summary of current research in the application of image registration to satellite imagery. Presenting algorithms for creating mosaics and tracking changes on the planet's surface over time, it is an indispensable resource for researchers and advanced students in Earth and space science, and image processing.
Image registration is a digital image 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, 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 specialized graduate courses.
Arvustused
'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
Muu info
Demonstrates the application of image registration for creating mosaics of satellite images and tracking temporal changes at the Earth's surface.
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ix | |
| Foreword |
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xii | |
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| Acknowledgements |
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xiv | |
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PART I The Importance of Image Registration for Remote Sensing |
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3 | (21) |
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2 Influence of image registration on validation efforts |
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24 | (11) |
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3 Survey of image registration methods |
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35 | (44) |
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PART II Similarity Metrics for Image Registration |
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4 Fast correlation and phase correlation |
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79 | (33) |
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5 Matched filtering techniques |
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112 | (19) |
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6 Image registration using mutual information |
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131 | (22) |
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PART III Feature Matching and Strategies for Image Registration |
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7 Registration of multiview images |
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153 | (26) |
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8 New approaches to robust, point-based image registration |
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179 | (21) |
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9 Condition theory for image registration and post-registration error estimation |
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200 | (15) |
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10 Feature-based image to image registration |
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215 | (25) |
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11 On the use of wavelets for image registration |
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240 | (25) |
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12 Gradient descent approaches to image registration |
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265 | (11) |
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13 Bounding the performance of image registration |
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276 | (17) |
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PART IV Applications and Operational Systems |
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14 Multitemporal and multisensor image registration |
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293 | (46) |
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15 Georegistration of meteorological images |
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339 | (16) |
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16 Challenges, solutions, and applications of accurate multiangle image registration: Lessons learned from MISR |
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355 | (28) |
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17 Automated AVHRR image navigation |
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383 | (17) |
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18 Landsat image geocorrection and registration |
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400 | (15) |
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19 Automatic and precise orthorectification of SPOT images |
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415 | (11) |
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20 Geometry of the VEGETATION sensor |
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426 | (11) |
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21 Accurate MODIS global geolocation through automated ground control image matching |
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437 | (19) |
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22 SeaWiFS operational geolocation assessment system |
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456 | (19) |
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475 | (3) |
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| Index |
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478 | |
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 Geoscience and Remote Sensing and other remote sensing venues.
