Low-Altitude Photogrammetry and Remote Sensing in UAV for Improving Mapping Accuracy

The low-altitude photogrammetry technology of unmanned aerial vehicles (UAVs) is widely used in many fields, but the absence of analysis and research affects the accuracy of its data products. At the same time, low-altitude photogrammetry faces the problem of low elevation positioning accuracy. The network space triangulation adjustment in the beam technique region is considered to eliminate perspective distortion in non-overlapping areas. This paper explains the key technologies of low-altitude photography and remote sensing mapping of UAVs, rectifies the distortion difference of remote sensing images, and then carries out grid division on the image according to the improved APAP (as-projective-as-possible warp) matching method. Next, it solves each grid homography matrix, linearizes the homography matrix, and carries out image matching according to the linearized homography matrix, which can effectively weaken the ghosting phenomenon during image matching. The network space triangulation adjustment in the beam technique region is considered to eliminate perspective distortion in non-overlapping areas. The two measurement areas' accuracy level is analyzed using digital line drawing and digital orthophoto images (DOIs). Finally, the experimental results indicate that the image matching algorithm proposed in this paper has strong reliability and can substantially increase photogrammetric elevation positioning.