Automatic UAV Image Geo-Registration by Matching UAV Images to Georeferenced Image Data

Tobias Koch,Peter Reinartz,Friedrich Fraundorfer,Franz Kurz,Xiangyu Zhuo

doi:10.3390/rs9040376

Abstract

Recent years have witnessed the fast development of UAVs (unmanned aerial vehicles). As an alternative to traditional image acquisition methods, UAVs bridge the gap between terrestrial and airborne photogrammetry and enable flexible acquisition of high resolution images. However, the georeferencing accuracy of UAVs is still limited by the low-performance on-board GNSS and INS. This paper investigates automatic geo-registration of an individual UAV image or UAV image blocks by matching the UAV image(s) with a previously taken georeferenced image, such as an individual aerial or satellite image with a height map attached or an aerial orthophoto with a DSM (digital surface model) attached. As the biggest challenge for matching UAV and aerial images is in the large differences in scale and rotation, we propose a novel feature matching method for nadir or slightly tilted images. The method is comprised of a dense feature detection scheme, a one-to-many matching strategy and a global geometric verification scheme. The proposed method is able to find thousands of valid matches in cases where SIFT and ASIFT fail. Those matches can be used to geo-register the whole UAV image block towards the reference image data. When the reference images offer high georeferencing accuracy, the UAV images can also be geolocalized in a global coordinate system. A series of experiments involving different scenarios was conducted to validate the proposed method. The results demonstrate that our approach achieves not only decimeter-level registration accuracy, but also comparable global accuracy as the reference images.

Highlights

Emerging as novel image acquisition platforms, unmanned aerial vehicles (UAVs) bridge the gap between aerial and terrestrial photogrammetry and offer an alternative to conventional airborne image acquisition systems
The results demonstrate that our approach achieves decimeter-level co-registration accuracy and comparable absolute geo-registration accuracy as the reference image
This paper investigates into UAV geo-registration by matching UAV images with already georeferenced aerial imagery

Summary

Introduction

Emerging as novel image acquisition platforms, unmanned aerial vehicles (UAVs) bridge the gap between aerial and terrestrial photogrammetry and offer an alternative to conventional airborne image acquisition systems. In comparison to airborne or satellite remote sensing, UAVs stand out for low cost, the utility to be used in hazardous or inaccessible areas and the ability to achieve high spatial and temporal resolutions. In contrast with manned aircraft, UAVs have smaller coverage due to lower flight altitude, but they are able to achieve high ground sampling distance (GSD) with lower cost and better flexibility. While manned aircraft require big landing fields and pilots, UAVs only need small landing sites and can be remotely controlled; they can work even in hazardous areas and severe weather conditions. UAVs have been widely involved in remote sensing applications, such as disaster management, urban development, documentation of cultural heritage or agriculture management [3]

Methods

Results

Discussion

Conclusion