Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/182147
Title: Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery
Authors: Pak, Hui Ying
Lin, Weisi
Law, Adrian Wing-Keung
Keywords: Engineering
Issue Date: 2024
Source: Pak, H. Y., Lin, W. & Law, A. W. (2024). Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery. International Journal of Remote Sensing. https://dx.doi.org/10.1080/01431161.2024.2440944
Journal: International Journal of Remote Sensing 
Abstract: Mosaicking of Unmanned Aerial Vehicles (UAV) imagery over featureless water bodies has been known to be challenging, and poses a significant impediment to water monitoring applications. Techniques such as Structure-from-motion typically fail under such conditions due to the lack of distinctive features in the scene, and direct georeferencing is currently the only practical solution, albeit lower georeferencing accuracy is expected. However, hardware issues, particularly the typical time delay between the GPS unit and the image capture, can lead to systematic image misalignment and further reducing the accuracy. The systematic image misalignment arises as the recording of the geographical coordinates by the GPS unit may not precisely correspond to the exact moment of image exposure, and the image exposure may not always occur at the mid-exposure time. Hardware solutions can mitigate this issue but require technical expertise and resources. Alternatively, software solutions can address the problem without necessitating any hardware modifications. This study introduces an open-source solution for the correction of the systematic image alignment by accounting for the time delay and distance discrepancy between the measurements of the GPS coordinates and the image capture. The method was validated with field UAV surveys conducted in this study under various flight configurations (different flight altitudes and overlap ratios), and effective image alignment was obtained using the proposed open-source solution which reduced the georeferencing error by around 67.7%. Specifically, a georeferencing error of RMSE = 1.409 m and (Formula presented.) = 0.6356 m was achieved without the use of any ground control points (GCPs). Finally, as demonstrated in this study, low flight altitudes (e.g. 15 m) should be discouraged for such conditions as georeferencing errors could amplify due to the limited accuracy of the GPS, resulting in visual artefacts.
URI: https://hdl.handle.net/10356/182147
ISSN: 0143-1161
DOI: 10.1080/01431161.2024.2440944
Schools: School of Civil and Environmental Engineering 
Interdisciplinary Graduate School (IGS) 
School of Computer Science and Engineering 
Research Centres: Environmental Process Modelling Centre 
Nanyang Environment and Water Research Institute
Rights: © 2024 Informa UK Limited, trading as Taylor & Francis Group. All rights reserved. This article may be downloaded for personal use only. Any other use requires prior permission of the copyright holder. The Version of Record is available online at http://doi.org/10.1080/01431161.2024.2440944.
Fulltext Permission: embargo_20260103
Fulltext Availability: With Fulltext
Appears in Collections:CEE Journal Articles

Files in This Item:
File Description SizeFormat 
Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery.pdf
  Until 2026-01-03
Main text1.38 MBAdobe PDFUnder embargo until Jan 03, 2026
Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery APPENDIX.pdf
  Until 2026-01-03
Appendix335.59 kBAdobe PDFUnder embargo until Jan 03, 2026

Page view(s)

27
Updated on Jan 23, 2025

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.