A General Framework of Remote Sensing Epipolar Image Generation
Epipolar images can improve the efficiency and accuracy of dense matching by restricting the search range of correspondences from 2-D to 1-D, which play an important role in 3-D reconstruction. As most of the satellite images in archives are incidental collections, which do not have rigorous stereo...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-11-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/13/22/4539 |
| _version_ | 1797508562146033664 |
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| author | Xuanqi Wang Feng Wang Yuming Xiang Hongjian You |
| author_facet | Xuanqi Wang Feng Wang Yuming Xiang Hongjian You |
| author_sort | Xuanqi Wang |
| collection | DOAJ |
| description | Epipolar images can improve the efficiency and accuracy of dense matching by restricting the search range of correspondences from 2-D to 1-D, which play an important role in 3-D reconstruction. As most of the satellite images in archives are incidental collections, which do not have rigorous stereo properties, in this paper, we propose a general framework to generate epipolar images for both in-track and cross-track stereo images. We first investigate the theoretical epipolar constraints of single-sensor and multi-sensor images and then introduce the proposed framework in detail. Considering large elevation changes in mountain areas, the publicly available digital elevation model (DEM) is applied to reduce the initial offsets of two stereo images. The left image is projected into the image coordinate system of the right image using the rational polynomial coefficients (RPCs). By dividing the raw images into several blocks, the epipolar images of each block are parallel generated through a robust feature matching method and fundamental matrix estimation, in which way, the horizontal disparity can be drastically reduced while maintaining negligible vertical disparity for epipolar blocks. Then, stereo matching using the epipolar blocks can be easily implemented and the forward intersection method is used to generate the digital surface model (DSM). Experimental results on several in-track and cross-track images, including optical-optical, SAR-SAR, and SAR-optical pairs, demonstrate the effectiveness of the proposed framework, which not only has obvious advantages in mountain areas with large elevation changes but also can generate high-quality epipolar images for flat areas. The generated epipolar images of a ZiYuan-3 pair in Songshan are further utilized to produce a high-precision DSM. |
| first_indexed | 2024-03-10T05:05:41Z |
| format | Article |
| id | doaj.art-12d427201c994be697c696905bb92eb6 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T05:05:41Z |
| publishDate | 2021-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-12d427201c994be697c696905bb92eb62023-11-23T01:19:00ZengMDPI AGRemote Sensing2072-42922021-11-011322453910.3390/rs13224539A General Framework of Remote Sensing Epipolar Image GenerationXuanqi Wang0Feng Wang1Yuming Xiang2Hongjian You3Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaAerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, ChinaEpipolar images can improve the efficiency and accuracy of dense matching by restricting the search range of correspondences from 2-D to 1-D, which play an important role in 3-D reconstruction. As most of the satellite images in archives are incidental collections, which do not have rigorous stereo properties, in this paper, we propose a general framework to generate epipolar images for both in-track and cross-track stereo images. We first investigate the theoretical epipolar constraints of single-sensor and multi-sensor images and then introduce the proposed framework in detail. Considering large elevation changes in mountain areas, the publicly available digital elevation model (DEM) is applied to reduce the initial offsets of two stereo images. The left image is projected into the image coordinate system of the right image using the rational polynomial coefficients (RPCs). By dividing the raw images into several blocks, the epipolar images of each block are parallel generated through a robust feature matching method and fundamental matrix estimation, in which way, the horizontal disparity can be drastically reduced while maintaining negligible vertical disparity for epipolar blocks. Then, stereo matching using the epipolar blocks can be easily implemented and the forward intersection method is used to generate the digital surface model (DSM). Experimental results on several in-track and cross-track images, including optical-optical, SAR-SAR, and SAR-optical pairs, demonstrate the effectiveness of the proposed framework, which not only has obvious advantages in mountain areas with large elevation changes but also can generate high-quality epipolar images for flat areas. The generated epipolar images of a ZiYuan-3 pair in Songshan are further utilized to produce a high-precision DSM.https://www.mdpi.com/2072-4292/13/22/4539DEMepipolar constraintRPCsepipolar imageDSMstereo matching |
| spellingShingle | Xuanqi Wang Feng Wang Yuming Xiang Hongjian You A General Framework of Remote Sensing Epipolar Image Generation Remote Sensing DEM epipolar constraint RPCs epipolar image DSM stereo matching |
| title | A General Framework of Remote Sensing Epipolar Image Generation |
| title_full | A General Framework of Remote Sensing Epipolar Image Generation |
| title_fullStr | A General Framework of Remote Sensing Epipolar Image Generation |
| title_full_unstemmed | A General Framework of Remote Sensing Epipolar Image Generation |
| title_short | A General Framework of Remote Sensing Epipolar Image Generation |
| title_sort | general framework of remote sensing epipolar image generation |
| topic | DEM epipolar constraint RPCs epipolar image DSM stereo matching |
| url | https://www.mdpi.com/2072-4292/13/22/4539 |
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