Airborne Optical Sectioning

Abstract

Drones are becoming increasingly popular for remote sensing of landscapes in archeology, cultural heritage, forestry, and other disciplines. They are more efficient than airplanes for capturing small areas, of up to several hundred square meters. LiDAR (light detection and ranging) and photogrammetry have been applied together with drones to achieve 3D reconstruction. With airborne optical sectioning (AOS), we present a radically different approach that is based on an old idea: synthetic aperture imaging. Rather than measuring, computing, and rendering 3D point clouds or triangulated 3D meshes, we apply image-based rendering for 3D visualization. In contrast to photogrammetry, AOS does not suffer from inaccurate correspondence matches and long processing times. It is cheaper than LiDAR, delivers surface color information, and has the potential to achieve high sampling resolutions. AOS samples the optical signal of wide synthetic apertures (30-100 m diameter) with unstructured video images recorded from a low-cost camera drone to support optical sectioning by image integration. The wide aperture signal results in a shallow depth of field and consequently in a strong blur of out-of-focus occluders, while images of points in focus remain clearly visible. Shifting focus computationally towards the ground allows optical slicing through dense occluder structures (such as leaves, tree branches, and coniferous trees), and discovery and inspection of concealed artifacts on the surface.

A Statistical View on Synthetic Aperture Imaging for Occlusion Removal

“…10. Synthetic aperture rendering results of the AOS scan presented in [21] for different a, N combinations that satisfy the baseline suggested by our model (b = 2.8 m). Visual difference to the fully sampled case (a = 50 m, N = 504) is indicated by SSIM [27].…”

“…1 illustrates an example where AOS was used to uncover the ruins of a 19th century fortification system that is concealed by dense forest and shrubs. The interested reader is referred to [21], [22] for more details.…”

Fast Automatic Visibility Optimization for Thermal Synthetic Aperture Visualization

“…Consequently, objects above and below the focal plane (e.g., occluders) are suppressed while objects on the focal plane are amplified and become more visible. See [3] and [2] for more details on the image integration process and the statistical principles and of AOS.…”

Thermal Airborne Optical Sectioning

“…With airborne optical sectioning (AOS) [21,22], we apply camera drones for synthetic aperture imaging. They sample the optical signal of wide synthetic apertures (up to 100 m diameter) with multiscopic video images as an unstructured (irregularly sampled) light field to support optical slicing by image integration.…”

“…Thus, 0.18 pixels is the average misalignment between the 10 thermal images when they are computationally integrated for AOS. Considering an approximate distance of 11 m to our target, the spatial sampling resolution of TAOS in this experiment was 1408 pixels m −2 (considering the size of thermal pixels, the uncertainty due to errors in pose estimation [21], and the distance to the target).…”