Accurate and robust stereovision with a large number of aerial images
D. Canu, Nicholas Ayache, J. A. Sirat · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
Automatic computation of 3D reconstruction of scenes is traditionally based on the use of the normalized cross-correlation technique to match stereoscopic images. This matching technique called area-based matching technique allows to retrieve which pixels on images are the projection of the same 3D point of the analyzed scene. In the case of high resolution stereoscopic images which include a ground resolution up to a few decimeters, the matching problem is more difficult because of the presence shadow areas, hidden parts, important discontinuities in the 3D structures and textureless or repetitive-texture regions. These characteristics of high resolution stereoscopic images appear as real obstacles to the area-based matching technique with binocular stereovision approach. In this paper, we present a novel method to compare a dense scene 3D reconstruction from a large number of aerial images. It achieves robust and accurate reconstruction and deals with local occlusions and surface discontinuities. The principle of the algorithm is based on the simultaneous matching of images with a cross-correlation technique. The location of each cameras is unconstrained and a calibration stage is used to retrieve the epipolar geometry. We finally show the feasibility of this approach to produce robust and accurate matchings on results achieved with synthetic and real images.