Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery
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 featu...
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sg-ntu-dr.10356-1821472025-01-10T15:34:54Z Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery Pak, Hui Ying Lin, Weisi Law, Adrian Wing-Keung School of Civil and Environmental Engineering Interdisciplinary Graduate School (IGS) School of Computer Science and Engineering Environmental Process Modelling Centre Nanyang Environment and Water Research Institute Engineering Aerial vehicle Altitude control 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. National Research Foundation (NRF) Public Utilities Board (PUB) Submitted/Accepted version This research/project is supported by the National Research Foundation, Singapore, and PUB,Singapore’s National Water Agency under its RIE2025 Urban Solutions and Sustainability (USS)(Water) Centre of Excellence (CoE) Programme, awarded to Nanyang Environment & WaterResearch Institute (NEWRI), Nanyang Technological University, Singapore (NTU). 2025-01-10T08:02:51Z 2025-01-10T08:02:51Z 2024 Journal Article 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 0143-1161 https://hdl.handle.net/10356/182147 10.1080/01431161.2024.2440944 2-s2.0-85213060085 en International Journal of Remote Sensing © 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. application/pdf application/pdf |
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Engineering Aerial vehicle Altitude control |
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Engineering Aerial vehicle Altitude control Pak, Hui Ying Lin, Weisi Law, Adrian Wing-Keung Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery |
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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. |
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School of Civil and Environmental Engineering |
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School of Civil and Environmental Engineering Pak, Hui Ying Lin, Weisi Law, Adrian Wing-Keung |
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Article |
author |
Pak, Hui Ying Lin, Weisi Law, Adrian Wing-Keung |
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Pak, Hui Ying |
title |
Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery |
title_short |
Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery |
title_full |
Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery |
title_fullStr |
Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery |
title_full_unstemmed |
Correction of systematic image misalignment in direct georeferencing of UAV multispectral imagery |
title_sort |
correction of systematic image misalignment in direct georeferencing of uav multispectral imagery |
publishDate |
2025 |
url |
https://hdl.handle.net/10356/182147 |
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1821237120218431488 |