The accurate measurement of the exterior orientation of remote sensing systems is essential for the quality of the resulting imagery products. Fast orientation changes of the camera immediately before, during or after image acquisition are still serious problems in aerial and satellite based remote sensing. This is due to the fact that in many cases such orientation changes can neither be suppressed effectively nor measured adequately with conventional technology at reasonable costs. In this article, an approach for an auxiliary orientation measurement system is presented that is able to measure a remote sensing system’s orientation changes with both, a very high rate and appropriate precision. Two or more auxiliary image sensors are used to measure the orientation changes on the basis of the shift in their images. It is shown that these shifts can be determined by tracking suitable point features through a series of images in real time using a standard mobile CPU for up to 480 images per second. From these shifts the orientation of the whole system can be derived and offset-corrected by conventional orientation measurements. The approach was tested on a test flight with the DLR’s MFC line camera and two auxiliary high-speed CMOS cameras. The results are presented and compared to the reference measurements of a high-end INS/GPS system.
[1]
Klaus Janschek,et al.
Airborne test results for smart pushbroom imaging system with optoelectronic image correction
,
2004,
SPIE Remote Sensing.
[2]
C Tomasi,et al.
Shape and motion from image streams: a factorization method.
,
1992,
Proceedings of the National Academy of Sciences of the United States of America.
[3]
Börner Anko,et al.
MFC: a modular line camera for 3D world modulling
,
2008
.
[4]
J.-Y. Bouguet,et al.
Pyramidal implementation of the lucas kanade feature tracker
,
1999
.
[5]
Karsten Scheibe,et al.
MFC - A Modular Line Camera for 3D World Modulling
,
2008,
RobVis.
[6]
Jürgen Wohlfeil,et al.
A modular, interactive software-concept for radiometric and geometric correction of airborne and spaceborne linescanner images
,
2009,
Remote Sensing.
[7]
Carlo Tomasi,et al.
Good features to track
,
1994,
1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.
[8]
Klaus Janschek,et al.
Optical Correlator for Image Motion Compensation in the Focal Plane of a Satellite Camera
,
2001
.