Book contents
- Frontmatter
- Contents
- List of contributors
- Foreword by Jón A. Benediktsson
- Acknowledgements
- PART I The Importance of Image Registration for Remote Sensing
- PART II Similarity Metrics for Image Registration
- PART III Feature Matching and Strategies for Image Registration
- PART IV Applications and Operational Systems
- 14 Multitemporal and multisensor image registration
- 15 Georegistration of meteorological images
- 16 Challenges, solutions, and applications of accurate multiangle image registration: Lessons learned from MISR
- 17 Automated AVHRR image navigation
- 18 Landsat image geocorrection and registration
- 19 Automatic and precise orthorectification of SPOT images
- 20 Geometry of the VEGETATION sensor
- 21 Accurate MODIS global geolocation through automated ground control image matching
- 22 SeaWiFS operational geolocation assessment system
- PART V Conclusion
- Index
- Plate section
- Plate section
- References
19 - Automatic and precise orthorectification of SPOT images
from PART IV - Applications and Operational Systems
Published online by Cambridge University Press: 03 May 2011
- Frontmatter
- Contents
- List of contributors
- Foreword by Jón A. Benediktsson
- Acknowledgements
- PART I The Importance of Image Registration for Remote Sensing
- PART II Similarity Metrics for Image Registration
- PART III Feature Matching and Strategies for Image Registration
- PART IV Applications and Operational Systems
- 14 Multitemporal and multisensor image registration
- 15 Georegistration of meteorological images
- 16 Challenges, solutions, and applications of accurate multiangle image registration: Lessons learned from MISR
- 17 Automated AVHRR image navigation
- 18 Landsat image geocorrection and registration
- 19 Automatic and precise orthorectification of SPOT images
- 20 Geometry of the VEGETATION sensor
- 21 Accurate MODIS global geolocation through automated ground control image matching
- 22 SeaWiFS operational geolocation assessment system
- PART V Conclusion
- Index
- Plate section
- Plate section
- References
Summary
Abstract
Following the SPOT-5 launch, Spot Image and the French National Geographic Institute (IGN) have designed a high-accuracy worldwide database called Reference3D™ using data from the High Resolution Stereoscopic (HRS) SPOT-5 instrument. This database consists of three information layers: A Digital Elevation Model (DEM) at 50-m resolution, ortho-images at 5-m resolution, and quality masks with a circular horizontal accuracy better than 16 m for 90% of the points and an elevation accuracy better than 10 m for 90% of the points. A new system (called ANDORRE) was also developed to archive the Reference3D™ database and to automatically produce orthorectified images using Reference3D™ data. ANDORRE takes advantage of Reference3D™ horizontal and vertical accuracies to automatically register and rectify an image from any SPOT satellite in every area where Reference3D™ data are available. This chapter presents the automatic orthorectification algorithm, developed under the CNES (French Space Agency) leadership, that is composed of three main steps: (1) Generation of a reference image (in focal plane geometry) using Reference3D™ orthoimage and DEM layers, (2) modeling of the misregistration between the reference image and the SPOT image to be processed, and (3) resampling of the image into a cartographic reference frame. It also describes the geometric performance measured on operational cases involving different landscapes, DEM data, and image resolutions. Timing measurements show that the rectification of a 24,000 × 24,000 image can be performed in less than an hour.
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- Chapter
- Information
- Image Registration for Remote Sensing , pp. 415 - 425Publisher: Cambridge University PressPrint publication year: 2011