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A radiometric block adjustment method for unmanned aerial vehicle images considering the image vignetting

A radiometric block adjustment method for unmanned aerial vehicle images considering the image vignetting
A radiometric block adjustment method for unmanned aerial vehicle images considering the image vignetting

Unmanned aerial vehicles (UAVs) equipped with different sensors can provide data with high spatiotemporal resolution and have broad application prospects. During the flight of the UAV, changes in illumination, exposure time, etc., will cause different degrees of radiometric differences between images, resulting in a calibration relationship established on a single image that cannot be applied to other images; in addition, the vignetting effect also significantly changes the brightness distribution inside an image, thus posing challenges for radiometric calibration of UAV images. In this article, based on block adjustment (BA), we proposed a radiometric BA model under the consideration of vignetting and the light-dark differences between images. The proposed method requires only a small number of calibration blankets, thus reducing the complexity of the experiment. The results from two study areas showed that the proposed method could compensate for vignetting to a certain extent and the radiometric consistency of the two datasets was improved from 12.9%-21.8% to 4.7%-12.7%. Validated using ground samples, the mean root mean square error (RMSE) and mean relative percent error (MRPE) of all five bands were 0.054, 21.8%, and 0.037, 20.4% in the two study areas, respectively. The total uncertainty was less than 8.1%. When there were obvious light-dark differences between images, such as in the visible light bands, our method could significantly improve the accuracy of the radiometric calibration.

Autonomous aerial vehicles, Calibration, Lighting, Radiometry, Reflectivity, Roads, Sensors, block adjustment (BA), light-dark differences, radiometric calibration, unmanned aerial vehicles (UAVs), vignetting, Block adjustment (BA)
0196-2892
Peng, Wanshan
9be0ca4d-5e33-4574-9dbf-5b9393b8f8bd
Gong, Yan
82046073-464e-4c0c-b821-9ee97c6cf106
Fang, Shenghui
1f470e8c-1631-411e-8d64-3f7850bd7b18
Zhang, Yongjun
d91b7181-69a5-476b-9d27-4255d7338722
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Ren, Jie
ee420bf5-1c19-4d47-a314-cdb9670e39a4
Mo, Jiacai
30540e1c-5327-42bb-abb0-c02d0c3fe62f
Peng, Wanshan
9be0ca4d-5e33-4574-9dbf-5b9393b8f8bd
Gong, Yan
82046073-464e-4c0c-b821-9ee97c6cf106
Fang, Shenghui
1f470e8c-1631-411e-8d64-3f7850bd7b18
Zhang, Yongjun
d91b7181-69a5-476b-9d27-4255d7338722
Dash, Jadunandan
51468afb-3d56-4d3a-aace-736b63e9fac8
Ren, Jie
ee420bf5-1c19-4d47-a314-cdb9670e39a4
Mo, Jiacai
30540e1c-5327-42bb-abb0-c02d0c3fe62f

Peng, Wanshan, Gong, Yan, Fang, Shenghui, Zhang, Yongjun, Dash, Jadunandan, Ren, Jie and Mo, Jiacai (2023) A radiometric block adjustment method for unmanned aerial vehicle images considering the image vignetting. IEEE Transactions on Geoscience and Remote Sensing, 61, [5402514]. (doi:10.1109/TGRS.2023.3268036).

Record type: Article

Abstract

Unmanned aerial vehicles (UAVs) equipped with different sensors can provide data with high spatiotemporal resolution and have broad application prospects. During the flight of the UAV, changes in illumination, exposure time, etc., will cause different degrees of radiometric differences between images, resulting in a calibration relationship established on a single image that cannot be applied to other images; in addition, the vignetting effect also significantly changes the brightness distribution inside an image, thus posing challenges for radiometric calibration of UAV images. In this article, based on block adjustment (BA), we proposed a radiometric BA model under the consideration of vignetting and the light-dark differences between images. The proposed method requires only a small number of calibration blankets, thus reducing the complexity of the experiment. The results from two study areas showed that the proposed method could compensate for vignetting to a certain extent and the radiometric consistency of the two datasets was improved from 12.9%-21.8% to 4.7%-12.7%. Validated using ground samples, the mean root mean square error (RMSE) and mean relative percent error (MRPE) of all five bands were 0.054, 21.8%, and 0.037, 20.4% in the two study areas, respectively. The total uncertainty was less than 8.1%. When there were obvious light-dark differences between images, such as in the visible light bands, our method could significantly improve the accuracy of the radiometric calibration.

Text
TGRS-2022-03489.R1_Proof_hi - Accepted Manuscript
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More information

e-pub ahead of print date: 18 April 2023
Published date: 18 April 2023
Additional Information: Publisher Copyright: © 1980-2012 IEEE.
Keywords: Autonomous aerial vehicles, Calibration, Lighting, Radiometry, Reflectivity, Roads, Sensors, block adjustment (BA), light-dark differences, radiometric calibration, unmanned aerial vehicles (UAVs), vignetting, Block adjustment (BA)

Identifiers

Local EPrints ID: 478908
URI: http://eprints.soton.ac.uk/id/eprint/478908
ISSN: 0196-2892
PURE UUID: 0892d676-6fcc-4ece-91f5-3d507b3109bc
ORCID for Jadunandan Dash: ORCID iD orcid.org/0000-0002-5444-2109

Catalogue record

Date deposited: 13 Jul 2023 16:42
Last modified: 17 Mar 2024 02:58

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Contributors

Author: Wanshan Peng
Author: Yan Gong
Author: Shenghui Fang
Author: Yongjun Zhang
Author: Jadunandan Dash ORCID iD
Author: Jie Ren
Author: Jiacai Mo

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