Automatic Geolocation Correction of Satellite Imagery

详细信息    查看全文

• 作者：Ozge C. Ozcanli ; Yi Dong ; Joseph L. Mundy…
• 关键词：Georegistration ; Satellite imagery ; 3 ; D modeling ; RPC camera model ; Bias correction
• 刊名：International Journal of Computer Vision
• 出版年：2016
• 出版时间：February 2016
• 年：2016
• 卷：116
• 期：3
• 页码：263-277
• 全文大小：13,768 KB
• 参考文献：d’Angelo, P., & Reinartz, P. (2012). DSM based orientation of large stereo satellite image blocks. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 39, 209–214.CrossRef
  Dial, G., & Grodecki, J. (2005). RPC replacement camera models. In Proceedings of the ASPRS 2005 annual conference.
  Fraser, C. S., & Hanley, H. B. (2003). Bias compensation in rational functions for IKONOS satellite imagery. Photogrammetric Engineering and Remote Sensing, 69, 53–58.CrossRef
  Grodecki, J., & Dial, G. (2003). Block adjustment of high-resolution satellite images described by rational polynomials. Photogrammetric Engineering and Remote Sensing, 69, 59–68.CrossRef
  Mikhail, E. M., Bethel, J. S., & McGlone, J. C. (2001). Introduction to modern photogrammetry. New York: Wiley.
  Oh, J., Toth, C., & Grejner-Brzezinska, D. (2010). Automatic georeferencing of aerial images using high-resolution stereo satellite images. In ASPRS annual conference.
  Pollard, T., & Mundy, J. L. (2007). Change detection in a 3-D world. In Proceedings of computer vision and pattern recognition (CVPR).
  Pollard, T., Eden, I., Mundy, J. L., & Cooper, D. B. (2010). A volumetric approach to change detection in satellite images. ASPRS Photogrammetric Engineering & Remote Sensing Journal, 76(7), 817–831.CrossRef
  Pritt, M. D., & LaTourette, K. J. (2011). Automated georegistration of motion imagery. In Applied imagery pattern recognition workshop (AIPR).
  Tom, V., Wallace, G. K., & Wolfe, G. J. (1983). Image registration by a statistical method. In Proceedings of SPIE applications of digital image processing VI (p. 432).
  
• 作者单位：Ozge C. Ozcanli (1)
  Yi Dong (1)
  Joseph L. Mundy (1)
  Helen Webb (2)
  Riad Hammoud (2)
  Victor Tom (2)
  
  1. Vision Systems, Inc., Providence, RI, USA
  2. BAE Systems, Burlington, MA, USA
  
• 刊物类别：Computer Science
• 刊物主题：Computer Imaging, Vision, Pattern Recognition and Graphics
  Artificial Intelligence and Robotics
  Image Processing and Computer Vision
  Pattern Recognition
  
• 出版者：Springer Netherlands
• ISSN：1573-1405

文摘

Modern satellites tag their images with geolocation information using GPS and star tracking systems. Depending on the quality of the geopositioning equipment, errors may range from a few meters to tens of meters on the ground. At the current state of art, there is no established method to automatically correct these errors limiting the large-scale joint utilization of cross-platform satellite images. In this paper, an automatic geolocation correction framework that corrects images from multiple satellites simultaneously is presented. As a result of the proposed correction process, all the images are effectively registered to the same absolute geodetic coordinate frame. The usability and the quality of the correction framework are demonstrated through a 3-D surface reconstruction application. The 3-D surface models given by original satellite geopositioning metadata, and the corrected metadata, are compared. The quality difference is measured through an entropy-based metric applied to the orthographic height maps given by the 3-D surface models. Measuring the absolute accuracy of the framework is harder due to lack of publicly available high-precision ground surveys. However, the geolocation of images of exemplar satellites from different parts of the globe are corrected, and the road networks given by OpenStreetMap are projected onto the images using original and corrected metadata to demonstrate the improved quality of alignment. Keywords Georegistration Satellite imagery 3-D modeling RPC camera model Bias correction