In the context of aerial imagery, one of the first steps toward a coherent processing of the information contained
in multiple images is geo-registration, which consists in assigning geographic 3D coordinates to the pixels of the
image. This enables accurate alignment and geo-positioning of multiple images, detection of moving objects
and fusion of data acquired from multiple sensors.
To solve this problem there are different approaches that
require, in addition to a precise characterization of the camera sensor, high resolution referenced images or terrain
elevation models, which are usually not publicly available or out of date. Building upon the idea of developing
technology that does not need a reference terrain elevation model, we propose a geo-registration technique that
applies variational methods to obtain a dense and coherent surface elevation model that is used to replace the
reference model. The surface elevation model is built by interpolation of scattered 3D points, which are obtained
in a two-step process following a classical stereo pipeline: first, coherent disparity maps between image pairs
of a video sequence are estimated and then image point correspondences are back-projected.
The proposed variational method enforces continuity of the disparity map not only along epipolar lines (as done by previous geo-registration techniques) but also across them, in the full 2D image domain. In the experiments, aerial images from synthetic video sequences have been used to validate the proposed technique