In-loop radial distortion compensation for long-term mosaicing of aerial videos

For the generation of overview panoramic images from aerial surveillance videos, registered video frames are stitched together. Assuming a planar landscape, feature points can be detected and used to estimate a homography. However, if the features are affected by radial distortion, their mapping depends on their position within the frame and the resulting homography becomes inaccurate. As a result, the length of aerial panorama images is typically restricted to several hundred frames. To overcome this issue, we derive a model for the joint estimation of several homographies and one constant radial distortion. Due to the computational complexity of the solution, we propose a fast, iterative algorithm. Based on geometrical constraints, we regularize the projection of a jointly estimated picture group. We present panorama images from uncalibrated aerial videos with more than 1500 frames.

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