Scanning Photogrammetry for Measuring Large Targets in Close Range

In close-range photogrammetry, images are difficult to acquire and organize primarily because of the limited field of view (FOV) of digital cameras when long focal lenses are used to measure large targets. To overcome this problem, we apply a scanning photography method that acquires images by rotating the camera in both horizontal and vertical directions at one station. This approach not only enlarges the FOV of each station but also ensures that all stations are distributed in order without coverage gap. We also conduct a modified triangulation according to the traits of the data overlapping among images from the same station to avoid matching all images with one another. This algorithm synthesizes the images acquired from the same station into synthetic images, which are then used to generate a free network. Consequently, we solve the exterior orientation elements of each original camera image in the free network and perform image matching among original images to obtain tie points. Finally, all original images are combined in self-calibration bundle adjustment with control points. The feasibility and precision of the proposed method are validated by testing it on two fields using 300 and 600 mm lenses. The results confirm that even with a small amount of control points, the developed scanning photogrammetry can steadily achieve millimeter scale accuracy at distances ranging from 40 m to 250 m.