Aerial Applications

The aerial imaging industry plays a major part in today’s world. It is constantly evolving and serves many different sectors and purposes for example, security, agriculture, transportation, real-estate, ecommerce and many more.

Unmanned aerial vehicles and systems have been popular for decades. In the past they were used mainly for military tasks but in recent years drones have become accessible and useful for other, wide civil applications.

The global commercial drone market value was estimated at 6.5 B US$ in 2020 and is expected to reach 34.5 B US$ by 2026.[1]

Aerial systems involve multiple aspects of computer vision. Since the company was established, Vision Elements have provided professional support for projects of aerial mapping, photogrammetry, 3D reconstruction, bundle adjustment, orthophotos, remote sensing, as well as LiDAR and point cloud manipulation.
All these aspects are at the core of airborne platforms.


By using aerial imagery, the Vision Elements team produces comprehensive visual and topographic mosaics. Photogrammetry allows valuable information to be gathered, processed, measured and interpreted, so that objects and patterns in images are scientifically identified. This information can serve multiple stakeholders. Additionally, aerial mapping allows us to build 3D models, high resolution aerial orthophotos, and includes LiDAR-generated point clouds as well as fusion of images and laser scans.


LiDAR technology allows us to measure ranges of detected objects and is nowadays implemented in multiple aerial mapping systems to generate digital elevation modelsĀ (DEM) and digital surface models (DSM).


Vision Elements develops systems capable of fusing hyper-spectral, thermal imaging and almost any available digital imagery, helping to bring drone output to new levels.

Our scientists have vast experience with data fusion from different sensors, calibration of measuring systems, sophisticated edge-preserving smoothing, photorealistic texturing, artefact removal, segmentation, deblurring, object tracking, and differential GPS georeferencing.


In addition to the above, 2D and 3D deep neural networks are used to combine larger data sets into valuable information otherwise harder to yield. This is crucial in systems deployed in drones.

As the world transitions and uses faster, more accurate and advanced technologies, these methods will become integral in different airborne platforms.