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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 | Size | Format | |
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Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery.pdf Until 2026-01-03 | Main text | 1.38 MB | Adobe PDF | Under embargo until Jan 03, 2026 |
Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery APPENDIX.pdf Until 2026-01-03 | Appendix | 335.59 kB | Adobe PDF | Under embargo until Jan 03, 2026 |
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