Fast Matching Method of UAV Aerial Photography Enhanced Low Illumination Image
Aiming at the problems of insufficient image contrast in three-dimensional reconstruction of UAV in low illumination environment and the unstable iteration times of the RANSAC algorithm in the feature matching process, real-time matching method of UAV aerial image is proposed. First, a new image enh...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/9543893 |
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| _version_ | 1832565579324588032 |
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| author | Wenyao Li Guangqing Liu Kuan Lu Pengyun Chen Junjie Cui Mingrang Yu Peng Shen |
| author_facet | Wenyao Li Guangqing Liu Kuan Lu Pengyun Chen Junjie Cui Mingrang Yu Peng Shen |
| author_sort | Wenyao Li |
| collection | DOAJ |
| description | Aiming at the problems of insufficient image contrast in three-dimensional reconstruction of UAV in low illumination environment and the unstable iteration times of the RANSAC algorithm in the feature matching process, real-time matching method of UAV aerial image is proposed. First, a new image enhancement algorithm is applied to the image to enhance its quality and visibility. Second, the enhanced fast algorithm in ORB extracts the feature points from the preprocessed image, and cross-matching performs rough matching. Finally, the PROSAC algorithm solves the homography matrix by selecting the highest quality interior points from the extracted feature points. To improve the matching accuracy, some exterior points that do not conform to the geometric characteristics of the image are removed based on the homography matrix and the set mismatch threshold. The results show that the improved ORB algorithm is applied to the low illumination environment of UAV aerial photography, the image matching accuracy in 3D reconstruction is improved, and the correct matching rate tends to 97.24~99.39%. The relevant research findings and conclusions provide a fast and effective method for UAV image matching in different low illumination environments. |
| format | Article |
| id | doaj-art-41bc0c0105344456baf4a5d13fcea256 |
| institution | Kabale University |
| issn | 1687-5974 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-41bc0c0105344456baf4a5d13fcea2562025-02-03T01:07:10ZengWileyInternational Journal of Aerospace Engineering1687-59742022-01-01202210.1155/2022/9543893Fast Matching Method of UAV Aerial Photography Enhanced Low Illumination ImageWenyao Li0Guangqing Liu1Kuan Lu2Pengyun Chen3Junjie Cui4Mingrang Yu5Peng Shen6School of Mechatronic EngineeringShandong Product Quality Inspection Research InstituteSchool of Mechatronic EngineeringSchool of Mechatronic EngineeringSchool of Mechatronic EngineeringSchool of Mechatronic EngineeringKey Laboratory of Submarine GeosciencesAiming at the problems of insufficient image contrast in three-dimensional reconstruction of UAV in low illumination environment and the unstable iteration times of the RANSAC algorithm in the feature matching process, real-time matching method of UAV aerial image is proposed. First, a new image enhancement algorithm is applied to the image to enhance its quality and visibility. Second, the enhanced fast algorithm in ORB extracts the feature points from the preprocessed image, and cross-matching performs rough matching. Finally, the PROSAC algorithm solves the homography matrix by selecting the highest quality interior points from the extracted feature points. To improve the matching accuracy, some exterior points that do not conform to the geometric characteristics of the image are removed based on the homography matrix and the set mismatch threshold. The results show that the improved ORB algorithm is applied to the low illumination environment of UAV aerial photography, the image matching accuracy in 3D reconstruction is improved, and the correct matching rate tends to 97.24~99.39%. The relevant research findings and conclusions provide a fast and effective method for UAV image matching in different low illumination environments.http://dx.doi.org/10.1155/2022/9543893 |
| spellingShingle | Wenyao Li Guangqing Liu Kuan Lu Pengyun Chen Junjie Cui Mingrang Yu Peng Shen Fast Matching Method of UAV Aerial Photography Enhanced Low Illumination Image International Journal of Aerospace Engineering |
| title | Fast Matching Method of UAV Aerial Photography Enhanced Low Illumination Image |
| title_full | Fast Matching Method of UAV Aerial Photography Enhanced Low Illumination Image |
| title_fullStr | Fast Matching Method of UAV Aerial Photography Enhanced Low Illumination Image |
| title_full_unstemmed | Fast Matching Method of UAV Aerial Photography Enhanced Low Illumination Image |
| title_short | Fast Matching Method of UAV Aerial Photography Enhanced Low Illumination Image |
| title_sort | fast matching method of uav aerial photography enhanced low illumination image |
| url | http://dx.doi.org/10.1155/2022/9543893 |
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