Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features
Automatic registration of remote sensing images is an important task, which requires the establishment of appropriate correspondence between the sensed image and the reference image. Nowadays, the trend of satellite remote sensing technology is shifting towards high-resolution hyperspectral imaging...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/17/6/1011 |
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| author | Xiaorong Zhang Siyuan Li Zhongyang Xing Binliang Hu Xi Zheng |
| author_facet | Xiaorong Zhang Siyuan Li Zhongyang Xing Binliang Hu Xi Zheng |
| author_sort | Xiaorong Zhang |
| collection | DOAJ |
| description | Automatic registration of remote sensing images is an important task, which requires the establishment of appropriate correspondence between the sensed image and the reference image. Nowadays, the trend of satellite remote sensing technology is shifting towards high-resolution hyperspectral imaging technology. Ever higher revisit cycles and image resolutions require higher accuracy and real-time performance for automatic registration. The push-broom payload is affected by the push-broom stability of the satellite platform and the elevation change of ground objects, and the obtained hyperspectral image may have distortions such as stretching or shrinking at different parts of the image. In order to solve this problem, a new automatic registration strategy for remote sensing hyperspectral images based on the combination of whole and local features of the image was established, and two granularity registrations were carried out, namely coarse-grained matching and fine-grained matching. The high-resolution spatial features are first employed for detecting scale-invariant features, while the spectral information is used for matching, and then the idea of image stitching is employed to fuse the image after fine registration to obtain high-precision registration results. In order to verify the proposed algorithm, a simulated on-orbit push-broom imaging experiment was carried out to obtain hyperspectral images with local complex distortions under different lighting conditions. The simulation results show that the proposed remote sensing hyperspectral image registration algorithm is superior to the existing automatic registration algorithms. The advantages of the proposed algorithm in terms of registration accuracy and real-time performance make it have a broad prospect for application in satellite ground application systems. |
| format | Article |
| id | doaj-art-52fe7702158f4e57bf213815bc4d4e96 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-52fe7702158f4e57bf213815bc4d4e962025-08-20T02:43:06ZengMDPI AGRemote Sensing2072-42922025-03-01176101110.3390/rs17061011Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local FeaturesXiaorong Zhang0Siyuan Li1Zhongyang Xing2Binliang Hu3Xi Zheng4Laboratory of Spectral Imaging Technology, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an 710119, ChinaLaboratory of Spectral Imaging Technology, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an 710119, ChinaFrontier Interdisciplinary College, National University of Defense Technology, Changsha 410073, ChinaLaboratory of Spectral Imaging Technology, Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an 710119, ChinaInstitute of Earth Environment, Chinese Academy of Sciences, Xi’an 710061, ChinaAutomatic registration of remote sensing images is an important task, which requires the establishment of appropriate correspondence between the sensed image and the reference image. Nowadays, the trend of satellite remote sensing technology is shifting towards high-resolution hyperspectral imaging technology. Ever higher revisit cycles and image resolutions require higher accuracy and real-time performance for automatic registration. The push-broom payload is affected by the push-broom stability of the satellite platform and the elevation change of ground objects, and the obtained hyperspectral image may have distortions such as stretching or shrinking at different parts of the image. In order to solve this problem, a new automatic registration strategy for remote sensing hyperspectral images based on the combination of whole and local features of the image was established, and two granularity registrations were carried out, namely coarse-grained matching and fine-grained matching. The high-resolution spatial features are first employed for detecting scale-invariant features, while the spectral information is used for matching, and then the idea of image stitching is employed to fuse the image after fine registration to obtain high-precision registration results. In order to verify the proposed algorithm, a simulated on-orbit push-broom imaging experiment was carried out to obtain hyperspectral images with local complex distortions under different lighting conditions. The simulation results show that the proposed remote sensing hyperspectral image registration algorithm is superior to the existing automatic registration algorithms. The advantages of the proposed algorithm in terms of registration accuracy and real-time performance make it have a broad prospect for application in satellite ground application systems.https://www.mdpi.com/2072-4292/17/6/1011remotely sensed imageryhigh-resolution hyperspectral imagesimage auto-registrationimage stitching |
| spellingShingle | Xiaorong Zhang Siyuan Li Zhongyang Xing Binliang Hu Xi Zheng Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features Remote Sensing remotely sensed imagery high-resolution hyperspectral images image auto-registration image stitching |
| title | Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features |
| title_full | Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features |
| title_fullStr | Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features |
| title_full_unstemmed | Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features |
| title_short | Automatic Registration of Remote Sensing High-Resolution Hyperspectral Images Based on Global and Local Features |
| title_sort | automatic registration of remote sensing high resolution hyperspectral images based on global and local features |
| topic | remotely sensed imagery high-resolution hyperspectral images image auto-registration image stitching |
| url | https://www.mdpi.com/2072-4292/17/6/1011 |
| work_keys_str_mv | AT xiaorongzhang automaticregistrationofremotesensinghighresolutionhyperspectralimagesbasedonglobalandlocalfeatures AT siyuanli automaticregistrationofremotesensinghighresolutionhyperspectralimagesbasedonglobalandlocalfeatures AT zhongyangxing automaticregistrationofremotesensinghighresolutionhyperspectralimagesbasedonglobalandlocalfeatures AT binlianghu automaticregistrationofremotesensinghighresolutionhyperspectralimagesbasedonglobalandlocalfeatures AT xizheng automaticregistrationofremotesensinghighresolutionhyperspectralimagesbasedonglobalandlocalfeatures |