Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI
Sentinel-1 synthetic aperture radar (SAR) imagery, with its wide-swath imaging capabilities, provides crucial data for large-area interferometric SAR (InSAR) surface deformation monitoring. Precise image coregistration is essential but computationally intensive, especially for time-series processing...
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| Format: | Article |
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IEEE
2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10768949/ |
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| author | Yonghui Kang Yonghong Zhang Hong'an Wu Jujie Wei Xiaoxue Sun Yue Zuo |
| author_facet | Yonghui Kang Yonghong Zhang Hong'an Wu Jujie Wei Xiaoxue Sun Yue Zuo |
| author_sort | Yonghui Kang |
| collection | DOAJ |
| description | Sentinel-1 synthetic aperture radar (SAR) imagery, with its wide-swath imaging capabilities, provides crucial data for large-area interferometric SAR (InSAR) surface deformation monitoring. Precise image coregistration is essential but computationally intensive, especially for time-series processing. Current methods leveraging OpenMP for algorithm-level parallelism struggle with the large swaths and data volumes of Sentinel-1, limiting efficiency for practical applications. To address these challenges, this study introduces a multisegment parallel coregistration method combining OpenMP and MPI. The geometric coregistration process uses OpenMP and MPI for algorithm-level and multitask parallelism, boosting efficiency. In the enhanced spectral diversity coregistration, slave images are segmented by temporal baseline, with the first image processed serially and others in parallel. Validation with 30 Sentinel-1 SAR images from Tianjin-Tangshan (plain) and Zhejiang (mountainous) regions demonstrates significant improvements. OpenMP achieves optimal efficiency with 10-12 parallel kernels, while the combined OpenMP-MPI method performs best with 16 tasks for geometric coregistration and 24 for enhanced spectral diversity coregistration. The proposed method improves processing speeds by 8.2 and 6.7 times in plain regions and achieves comparable gains in mountainous areas, surpassing OpenMP alone. This approach effectively meets the efficiency demands of Sentinel-1 time-series coregistration. |
| format | Article |
| id | doaj-art-83e41204efc4427d885645167d44054b |
| institution | Kabale University |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-83e41204efc4427d885645167d44054b2025-01-16T00:00:21ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-01181656166910.1109/JSTARS.2024.350698010768949Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPIYonghui Kang0https://orcid.org/0009-0005-6657-0705Yonghong Zhang1https://orcid.org/0000-0002-1610-6710Hong'an Wu2https://orcid.org/0000-0003-1958-5654Jujie Wei3https://orcid.org/0000-0003-3626-393XXiaoxue Sun4https://orcid.org/0009-0008-8211-6950Yue Zuo5School of Geomatics, Liaoning Technical University, Fuxin, ChinaChinese Academy of Surveying and Mapping, Beijing, ChinaChinese Academy of Surveying and Mapping, Beijing, ChinaChinese Academy of Surveying and Mapping, Beijing, ChinaSchool of Geomatics, Liaoning Technical University, Fuxin, ChinaBeijing Guoxing Aerospace Technology Company Ltd., Beijing, ChinaSentinel-1 synthetic aperture radar (SAR) imagery, with its wide-swath imaging capabilities, provides crucial data for large-area interferometric SAR (InSAR) surface deformation monitoring. Precise image coregistration is essential but computationally intensive, especially for time-series processing. Current methods leveraging OpenMP for algorithm-level parallelism struggle with the large swaths and data volumes of Sentinel-1, limiting efficiency for practical applications. To address these challenges, this study introduces a multisegment parallel coregistration method combining OpenMP and MPI. The geometric coregistration process uses OpenMP and MPI for algorithm-level and multitask parallelism, boosting efficiency. In the enhanced spectral diversity coregistration, slave images are segmented by temporal baseline, with the first image processed serially and others in parallel. Validation with 30 Sentinel-1 SAR images from Tianjin-Tangshan (plain) and Zhejiang (mountainous) regions demonstrates significant improvements. OpenMP achieves optimal efficiency with 10-12 parallel kernels, while the combined OpenMP-MPI method performs best with 16 tasks for geometric coregistration and 24 for enhanced spectral diversity coregistration. The proposed method improves processing speeds by 8.2 and 6.7 times in plain regions and achieves comparable gains in mountainous areas, surpassing OpenMP alone. This approach effectively meets the efficiency demands of Sentinel-1 time-series coregistration.https://ieeexplore.ieee.org/document/10768949/Enhanced spectral diversitygeometric coregistrationmultisegmentparallel coregistrationSentinel-1 SAR images |
| spellingShingle | Yonghui Kang Yonghong Zhang Hong'an Wu Jujie Wei Xiaoxue Sun Yue Zuo Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Enhanced spectral diversity geometric coregistration multisegment parallel coregistration Sentinel-1 SAR images |
| title | Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI |
| title_full | Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI |
| title_fullStr | Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI |
| title_full_unstemmed | Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI |
| title_short | Multisegment Parallel Coregistration of Sentinel-1 SAR Time-Series Images by Combining OpenMP With MPI |
| title_sort | multisegment parallel coregistration of sentinel 1 sar time series images by combining openmp with mpi |
| topic | Enhanced spectral diversity geometric coregistration multisegment parallel coregistration Sentinel-1 SAR images |
| url | https://ieeexplore.ieee.org/document/10768949/ |
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