  The motivation of this paper is to address the problem of registering
airborne LiDAR data and optical aerial or satellite imagery acquired from
different platforms, at different times, with different points of view and
levels of detail. In this paper, we present a robust registration method based
on building regions, which are extracted from optical images using mean shift
segmentation, and from LiDAR data using a 3D point cloud filtering process. The
matching of the extracted building segments is then carried out using Graph
Transformation Matching (GTM) which allows to determine a common pattern of
relative positions of segment centers. Thanks to this registration, the
relative shifts between the data sets are significantly reduced, which enables
a subsequent fine registration and a resulting high-quality data fusion.
