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Geometric Correction of Unmanned Aerial Vehicle Hyperspectral Images Based on High-precision LiDAR Point Cloud
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Li-zhuang QI1, Jie PAN2, Qi LI1, *, Yi-zhuo ZHANG2, Jun-mei CHEN1, Xiao-han DONG1, Cheng-hao LIU1
Science Technology and Engineering | 2025, 25(17) : 7053 - 7060
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Science Technology and Engineering | 2025, 25(17): 7053-7060
Papers-Astronomy and Geosciences
Geometric Correction of Unmanned Aerial Vehicle Hyperspectral Images Based on High-precision LiDAR Point Cloud
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Li-zhuang QI1, Jie PAN2, Qi LI1, *, Yi-zhuo ZHANG2, Jun-mei CHEN1, Xiao-han DONG1, Cheng-hao LIU1
Affiliations
  • 1 Qilu Aerospace Information Research Institute, Jinan 250100, China
  • 2 Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Published: 2025-06-18 doi: 10.12404/j.issn.1671-1815.2405567
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Hyperspectral remote sensing widely uses unmanned aerial vehicles (UAV) as flight platforms for data collection, which has the advantages of flexibility and efficiency. However, due to UAV performance and environmental conditions, it is difficult for sensors to maintain a fixed shooting posture during the collection process, resulting in data misalignment, distortion, and deformation. While UAV positioning systems and inertial measurement devices provide real-time position and posture for hyperspectral cameras, achieving high accuracy often necessitates numerous ground control points for auxiliary geometric correction, which is time-consuming and labor-intensive. Therefore, it is necessary to study an efficient and time-saving data processing method to correct distortions in hyperspectral data acquisition. In order to efficiently and time-saving eliminate distortions in hyperspectral data during the acquisition process, an unmanned aerial vehicle (UAV) push scan hyperspectral camera data acquisition system was designed based on the principle of collinearity equations. The system integrates a high-precision inertial measurement system and synchronously collects LiDAR point cloud data in the measurement area. The high-precision terrain information contained in the LiDAR point cloud was used for geometric correction of hyperspectral data, and the influence of different density point cloud data on the geometric correction results was studied. Experiments have shown that using LiDAR point clouds improves accuracy by 67% compared to using average elevation geometric correction results. The use of LiDAR and hyperspectral cameras for synchronous acquisition has a significant effect on improving the accuracy of hyperspectral data.

hyperspectra  /  LiDAR  /  collinear equation  /  geometric correction
Li-zhuang QI, Jie PAN, Qi LI, Yi-zhuo ZHANG, Jun-mei CHEN, Xiao-han DONG, Cheng-hao LIU. Geometric Correction of Unmanned Aerial Vehicle Hyperspectral Images Based on High-precision LiDAR Point Cloud[J]. Science Technology and Engineering, 2025 , 25 (17) : 7053 -7060 . DOI: 10.12404/j.issn.1671-1815.2405567
Year 2025 volume 25 Issue 17
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doi: 10.12404/j.issn.1671-1815.2405567
  • Receive Date:2024-07-24
  • Online Date:2025-12-15
  • Published:2025-06-18
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  • Received:2024-07-24
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    1 Qilu Aerospace Information Research Institute, Jinan 250100, China
    2 Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
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表12种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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