An optical flow-based terrain extraction framework of VHR optical satellite stereo images
Stereo vision has attracted much interest in computer vision and remote sensing. Large-scale terrain extraction from optical satellites has achieved various applications due to the continuous development of optical satellite technology in the last forty years. This study analyzes the literature sour...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-11-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223003679 |
| _version_ | 1797633311246385152 |
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| author | Xinsheng Wang Mi Wang Yingdong Pi |
| author_facet | Xinsheng Wang Mi Wang Yingdong Pi |
| author_sort | Xinsheng Wang |
| collection | DOAJ |
| description | Stereo vision has attracted much interest in computer vision and remote sensing. Large-scale terrain extraction from optical satellites has achieved various applications due to the continuous development of optical satellite technology in the last forty years. This study analyzes the literature sources published in the last decade on stereo vision, optical flow, and remote sensing and finds that applications of the optical flow method in very high resolution (VHR) optical satellite stereo matching are inadequate. Therefore, it proposes a comprehensive optical flow-based terrain extraction framework from optical satellite stereo images. Experiments are conducted using stereo images from four different optical satellites, and the results are compared to the pertinent algorithms of ENVI, ERDAS, and ASP software. The qualitative and quantitative analysis demonstrates that the proposed method has significantly superior matching effect and robustness with a higher accuracy level compared with other approaches, especially for mountainous areas. In addition, the root mean square errors (RMSEs) of elevation on four datasets are 1.228 m, 2.159 m, 3.150 m, and 5.763 m, indicating the feasibility of the proposed method for terrain extraction from optical satellite stereo images. |
| first_indexed | 2024-03-11T11:52:19Z |
| format | Article |
| id | doaj.art-d6b65f8a23774c5dbedc1a12d2a64482 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-11T11:52:19Z |
| publishDate | 2023-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-d6b65f8a23774c5dbedc1a12d2a644822023-11-09T04:11:51ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-11-01124103543An optical flow-based terrain extraction framework of VHR optical satellite stereo imagesXinsheng Wang0Mi Wang1Yingdong Pi2State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, ChinaCorresponding author.; State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, ChinaStereo vision has attracted much interest in computer vision and remote sensing. Large-scale terrain extraction from optical satellites has achieved various applications due to the continuous development of optical satellite technology in the last forty years. This study analyzes the literature sources published in the last decade on stereo vision, optical flow, and remote sensing and finds that applications of the optical flow method in very high resolution (VHR) optical satellite stereo matching are inadequate. Therefore, it proposes a comprehensive optical flow-based terrain extraction framework from optical satellite stereo images. Experiments are conducted using stereo images from four different optical satellites, and the results are compared to the pertinent algorithms of ENVI, ERDAS, and ASP software. The qualitative and quantitative analysis demonstrates that the proposed method has significantly superior matching effect and robustness with a higher accuracy level compared with other approaches, especially for mountainous areas. In addition, the root mean square errors (RMSEs) of elevation on four datasets are 1.228 m, 2.159 m, 3.150 m, and 5.763 m, indicating the feasibility of the proposed method for terrain extraction from optical satellite stereo images.http://www.sciencedirect.com/science/article/pii/S1569843223003679Dense optical flowStereo visionOptical satellite stereo imagesEpipolar images |
| spellingShingle | Xinsheng Wang Mi Wang Yingdong Pi An optical flow-based terrain extraction framework of VHR optical satellite stereo images International Journal of Applied Earth Observations and Geoinformation Dense optical flow Stereo vision Optical satellite stereo images Epipolar images |
| title | An optical flow-based terrain extraction framework of VHR optical satellite stereo images |
| title_full | An optical flow-based terrain extraction framework of VHR optical satellite stereo images |
| title_fullStr | An optical flow-based terrain extraction framework of VHR optical satellite stereo images |
| title_full_unstemmed | An optical flow-based terrain extraction framework of VHR optical satellite stereo images |
| title_short | An optical flow-based terrain extraction framework of VHR optical satellite stereo images |
| title_sort | optical flow based terrain extraction framework of vhr optical satellite stereo images |
| topic | Dense optical flow Stereo vision Optical satellite stereo images Epipolar images |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223003679 |
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