Building Detection and Reconstruction from Mid- and High-Resolution Aerial Imagery
Résumé
In this paper, we discuss methods for building detection and reconstruction from aerial imagery. These methods are intended for the analysis of urban and suburban areas and have been applied to images of different resolutions (between 1 m and 10 cm per pixel). Various algorithms for image matching have been investigated, including hierarchical processing and new correlation schemes that have interesting properties for building recognition and building feature grouping. Cooperative combination of 2-D (monocular) and 3-D (stereoscopic) information allows the complete representation of the observed scene and particularly the detection of man-made raised structures such as buildings. A performance evaluation on simulation-based images has been considered in comparison with the corresponding ground truth reference. Our work illustrates that mid-resolution methods cannot be directly applied to high-resolution images. Classical algorithms must be adapted and new techniques have been defined to carry out dense urban area reconstruction.