GEOREFERENCING OF AERIAL IMAGERY

Abstract

Unmanned aerial vehicles, or UAVs, have completely changed the picture acquisition industry by offering a flexible way to take high-resolution pictures that successfully connect aerial and terrestrial photogrammetry. The precision of georeferencing, however, is a significant drawback in the use of UAVs, mainly because of the dependence on onboard GNSS (Global Navigation Satellite System) and INS (Inertial Navigation System) systems. Inaccuracies in GPS data and the inherent challenge of acquiring or identifying sufficient Ground Control Points (GCPs) can lead to georeferencing issues, hampering the reliability of UAV image data. Measurement and identifying GPCs are difficult and time-consuming. This thesis addresses this problem by giving a practical approach by introducing a feature-based matching method for the process of georeferencing aerial imagery under the photogrammetric pipeline. A near real-time georeferencing is done without using the GCPs, unlike traditional methods. The aerial images captured by UAVs are registered with the help of a previously georeferenced image, which is an orthophoto here. Digital Surface Models (DSMs) are also used to introduce the elevation factor. The method presents a different view and a substitute to georeferenced the images without establishing GCPs, especially in areas where it is hard to reach and requires more work for the conventional GCP setup method, which can be unaffordable as well. The pipeline in photogrammetry reduces the cost, improves the efficiency, and is suitable for vast applications, making this an interesting topic of study.