LAUSR

The recent development of structure-from-motion (SfM) and multi-view stereo (MVS) photogrammetry techniques has enabled semi-automatic high-resolution bathymetry using aerial images taken by consumer-grade digital cameras mounted on unmanned aerial vehicles (UAVs). However, the applicability of these techniques is sometimes limited by sun and sky reflections at the water surface, which render the point-cloud density and accuracy insufficient. In this research, we present a new imaging technique to suppress the effect of these water-surface reflections. In this technique, we order a drone to take a short video instead of a still picture at each waypoint. We then apply a temporal minimum filter to the video. This filter extracts the smallest RGB values in all the video frames for each pixel, and composes an image with greatly reduced reflection effects. To assess the performance of this technique, we applied it at three small shallow-water sites. Specifically, we evaluated the effect of the technique on the point cloud density and the accuracy and precision of the photogrammetry. The results showed that the proposed technique achieved a far denser point cloud than the case in which a randomly chosen frame was used for each waypoint, and also showed better overall accuracy and precision in estimating water-bottom elevation. The effectiveness of this new technique should depend on the surface wave state and sky radiance distribution, and this dependence, as well as the applicability to large areas, should be investigated in future research. Copyright © 2018 John Wiley & Sons, Ltd.