We present an efficient approach for finding homographies between sequences of aerial images. We propose a two-step approach: a) initially solving for image-plane rotation and scale parameters without using correspondence (under affine assumption), and b) using these parameters to constrain the full homography search, and c) extending the results to full perspective projection.
No flight meta-data, camera priors, or any other user defined information is used for the task. Based on the perspective parameters estimated, the aerial images are stitched with the best matching image based on a probabilistic model, to compose a high resolution aerial image mosaic. While retaining the improved asymptotic worst-case complexity of [6], we demonstrate significant performance improvements in practice.
Efficient Registration of Aerial Image Sequences Without Camera Priors
Asian Conference on Computer Vision ; 2007 ; Tokyo, Japan November 18, 2007 - November 22, 2007
2007-01-01
10 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Aerial Image , Normalize Cross Correlation , Harris Corner Detector , Registration Parameter , Seam Line Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence , Biometrics , Algorithm Analysis and Problem Complexity
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