AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS
Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR ima...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2017-09-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/651/2017/isprs-archives-XLII-2-W7-651-2017.pdf |
| _version_ | 1819083126880600064 |
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| author | Y. Xiang Y. Xiang W. Kang W. Kang F. Wang H. You H. You |
| author_facet | Y. Xiang Y. Xiang W. Kang W. Kang F. Wang H. You H. You |
| author_sort | Y. Xiang |
| collection | DOAJ |
| description | Due to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration
of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for
multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image
and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering
in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due
to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape
structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall
and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According
to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the
reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is
implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is
also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach
gives a robust and precise registration performance, compared with the orignal SAR-SIFT method. |
| first_indexed | 2024-12-21T20:27:37Z |
| format | Article |
| id | doaj.art-8698917455d74ce5b2c5326a0d09ab94 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-21T20:27:37Z |
| publishDate | 2017-09-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-8698917455d74ce5b2c5326a0d09ab942022-12-21T18:51:20ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342017-09-01XLII-2-W765165410.5194/isprs-archives-XLII-2-W7-651-2017AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREASY. Xiang0Y. Xiang1W. Kang2W. Kang3F. Wang4H. You5H. You6Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, ChinaKey Laboratory of Technology in Geo-spatial Information Processing and Application System, Institute of Electronics, Chinese Academy of Sciences, Beijing, ChinaUniversity of Chinese Academy of Sciences, Beijing, ChinaDue to the high resolution property and the side-looking mechanism of SAR sensors, complex buildings structures make the registration of SAR images in urban areas becomes very hard. In order to solve the problem, an automatic and robust coregistration approach for multiview high resolution SAR images is proposed in the paper, which consists of three main modules. First, both the reference image and the sensed image are segmented into two parts, urban areas and nonurban areas. Urban areas caused by double or multiple scattering in a SAR image have a tendency to show higher local mean and local variance values compared with general homogeneous regions due to the complex structural information. Based on this criterion, building areas are extracted. After obtaining the target regions, L-shape structures are detected using the SAR phase congruency model and Hough transform. The double bounce scatterings formed by wall and ground are shown as strong L- or T-shapes, which are usually taken as the most reliable indicator for building detection. According to the assumption that buildings are rectangular and flat models, planimetric buildings are delineated using the L-shapes, then the reconstructed target areas are obtained. For the orignal areas and the reconstructed target areas, the SAR-SIFT matching algorithm is implemented. Finally, correct corresponding points are extracted by the fast sample consensus (FSC) and the transformation model is also derived. The experimental results on a pair of multiview TerraSAR images with 1-m resolution show that the proposed approach gives a robust and precise registration performance, compared with the orignal SAR-SIFT method.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/651/2017/isprs-archives-XLII-2-W7-651-2017.pdf |
| spellingShingle | Y. Xiang Y. Xiang W. Kang W. Kang F. Wang H. You H. You AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS |
| title_full | AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS |
| title_fullStr | AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS |
| title_full_unstemmed | AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS |
| title_short | AUTOMATIC COREGISTRATION FOR MULTIVIEW SAR IMAGES IN URBAN AREAS |
| title_sort | automatic coregistration for multiview sar images in urban areas |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/651/2017/isprs-archives-XLII-2-W7-651-2017.pdf |
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