A project investigating
registration of aerial images with high definition ortho-imagery. Aerial
Images were first rectified to an orthographic viewing system, on the
basis of a telemetry file documenting the position of the aircraft at
the time of frame-capture. The orthorectified aerial image was then registered
with the OrthoGraphic Reference Imagery by computing high interest matchpoints
and finding correspondence. The error is calculated between the positions
of the points and is minimized using the Levenberg-Marquadet Minimization
Algorithm. An Update telemetry file is also generated in the process.
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We worked on developing
an image quality metric to work as a prescreener with their image registration
software. The idea is to filter out images that will be hard to register
before hand, so as not to waste resources during registration. Three image
quality metrics: SNR estimation, Texture measures, and Gabor energy, were
studied for five video clips of A. P. Hill area consisting of roughly
500 images. Using each image metric false positive, false negative, and
% misclassification were computed. Then these results were analyzed. Our
conclusion is that since Gabor measure is able to detect three major causes
of mission imagery failure: amount of texture, cloudy images, blurry images,
is more suitable than other two measures.
Richard W. Cannata, Mubarak Shah, Steven G. Blask, John A.
Van Workum. Autonomous
Video Registration Using Sensor Model Parameter Adjustments
, Applied
Imagery Pattern Recognition Workshop (AIPR) 2000, Cosmos Club, Washington
D.C., Oct 16-18, 2000
Workshop on Video Registration |