Direct Georeferencing for the Images in an Airborne LiDAR System by Automatic Boresight Misalignments Calibration

Abstract

Airborne Light Detection and Ranging (LiDAR) system and digital camera are usually integrated on a flight platform to obtain multi-source data. However, the photogrammetric system calibration is often independent of the LiDAR system and performed by the aerial triangulation method, which needs a test field with ground control points. In this paper, we present a method for the direct georeferencing of images collected by a digital camera integrated in an airborne LiDAR system by automatic boresight misalignments calibration with the auxiliary of point cloud. The method firstly uses an image matching to generate a tie point set. Space intersection is then performed to obtain the corresponding object coordinate values of the tie points, while the elevation calculated from the space intersection is replaced by the value from the LiDAR data, resulting in a new object point called Virtual Control Point (VCP). Because boresight misalignments exist, a distance between the tie point and the image point of VCP can be found by collinear equations in that image from which the tie point is selected. An iteration process is performed to minimize the distance with boresight corrections in each epoch, and it stops when the distance is smaller than a predefined threshold or the total number of epochs is reached. Two datasets from real projects were used to validate the proposed method and the experimental results show the effectiveness of the method by being evaluated both quantitatively and visually.

Extracting Urban Road Footprints from Airborne LiDAR Point Clouds with PointNet++ and Two-Step Post-Processing

“…Airborne light detection and ranging (LiDAR) is an active remote sensing technique for acquiring 3D geospatial data over the Earth's surface [1,2], with which a point clouds dataset encoding 3D coordinate values under a given geographic coordinate system can be generated [3]. The point clouds can be further processed to extract thematic information and to generate geo-mapping products, such as man-made objects [4], stand-alone plants [5], a digital elevation model (DEM) [6], etc.…”