Volume XXXIX-B1
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B1, 285-290, 2012
https://doi.org/10.5194/isprsarchives-XXXIX-B1-285-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXIX-B1, 285-290, 2012
https://doi.org/10.5194/isprsarchives-XXXIX-B1-285-2012
© Author(s) 2012. This work is distributed under
the Creative Commons Attribution 3.0 License.

  24 Jul 2012

24 Jul 2012

INTERIOR ORIENTATION ERROR MODELLING AND CORRECTION FOR PRECISE GEOREFERENCING OF SATELLITE IMAGERY

C. Zhang1, C. S. Fraser1, and S. Liu2 C. Zhang et al.
  • 1Cooperative Research Centre for Spatial Information, Dept. of Infrastructure Engineering, University of Melbourne, Australia
  • 2Department of Surveying and Geoinfomatics, Tongji University, Shanghai 200092, China

Keywords: High resolution, Satellite, Sensor, Imagery, Orientation, Modelling, Georeferencing, Accuracy

Abstract. To exploit full metric quality of optical satellite imagery, precise georeferencing is necessary. A number of sensor orientation models designed to exploit the full metric potential of images have been developed over the past decades. In particular, generic models attract more interest as they take full account of the physical imaging process by adopting time dependant satellite orbit models and interior orientation (IO) information provided by the satellite imagery vendors. The quality of IO parameters varies for different satellites and has significant impact on the georeferencing performance. Self-calibration approaches have been developed, however such approaches require a significant amount of ground control with good point distribution. In addition, the results are not always stable due to the correlation between the model parameters. In this paper, a simple yet efficient method has been proposed to correct the IO errors by detailed examination and efficient modelling of the IO error distribution in the focal plane. The proposed correction method, used in conjunction with a generic sensor model, significantly improves the metric performance of satellite images, leading to sub-pixel georeferencing accuracy.