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
14 - Multitemporal and multisensor image registration
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
Registration of multiple source imagery is one of the most important issues when dealing with Earth science remote sensing data where information from multiple sensors exhibiting various resolutions must be integrated. Issues ranging from different sensor geometries, different spectral responses, to various illumination conditions, various seasons and various amounts of noise, need to be dealt with when designing a new image registration algorithm. This chapter represents a first attempt at characterizing a framework that addresses these issues, in which possible choices for the three components of any registration algorithm are validated and combined to provide different registration algorithms. A few of these algorithms were tested on three different types of datasets – synthetic, multitemporal and multispectral. This chapter presents the results of these experiments and introduces a prototype registration toolbox.
Introduction
In Chapter 1, we showed how the analysis of Earth science data for applications, such as the study of global environmental changes, involves the comparison, fusion, and integration of multiple types of remotely sensed data at various temporal, spectral, and spatial resolutions. For such applications, the first required step is fast and automatic image registration which can provide precision correction of satellite imagery, band-to-band calibration, and data reduction for ease of transmission. Furthermore, future decision support systems, intelligent sensors and adaptive constellations will rely on real- or near-real-time interpretation of Earth observation data, performed both onboard and at ground-based stations.
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- Chapter
- Information
- Image Registration for Remote Sensing , pp. 293 - 338Publisher: Cambridge University PressPrint publication year: 2011
References
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