A Survey on SAR and Optical Satellite Image Registration
After decades of research, automatic synthetic aperture radar (SAR)-optical registration remains an unsolved problem. SAR and optical satellites utilize different imaging mechanisms, resulting in imagery with dissimilar heterogeneous characteristics. Transforming and translating these characteristic...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/3/850 |
| _version_ | 1827759591031570432 |
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| author | Oscar Sommervold Michele Gazzea Reza Arghandeh |
| author_facet | Oscar Sommervold Michele Gazzea Reza Arghandeh |
| author_sort | Oscar Sommervold |
| collection | DOAJ |
| description | After decades of research, automatic synthetic aperture radar (SAR)-optical registration remains an unsolved problem. SAR and optical satellites utilize different imaging mechanisms, resulting in imagery with dissimilar heterogeneous characteristics. Transforming and translating these characteristics into a shared domain has been the main challenge in SAR-optical matching for many years. Combining the two sensors will improve the quality of existing and future remote sensing applications across multiple industries. Several approaches have emerged as promising candidates in the search for combining SAR and optical imagery. In addition, recent research has indicated that machine learning-based approaches have great potential for filling the information gap posed by utilizing only one sensor type in Earth observation applications. However, several challenges remain, and combining them is a multi-step process where no one-size-fits-all approach is available. This article reviews traditional, state-of-the-art, and recent development trends in SAR-optical co-registration methods. |
| first_indexed | 2024-03-11T09:27:50Z |
| format | Article |
| id | doaj.art-e2150c51c27f4964927c8255b5000024 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T09:27:50Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-e2150c51c27f4964927c8255b50000242023-11-16T17:55:09ZengMDPI AGRemote Sensing2072-42922023-02-0115385010.3390/rs15030850A Survey on SAR and Optical Satellite Image RegistrationOscar Sommervold0Michele Gazzea1Reza Arghandeh2Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5020 Bergen, NorwayDepartment of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5020 Bergen, NorwayDepartment of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5020 Bergen, NorwayAfter decades of research, automatic synthetic aperture radar (SAR)-optical registration remains an unsolved problem. SAR and optical satellites utilize different imaging mechanisms, resulting in imagery with dissimilar heterogeneous characteristics. Transforming and translating these characteristics into a shared domain has been the main challenge in SAR-optical matching for many years. Combining the two sensors will improve the quality of existing and future remote sensing applications across multiple industries. Several approaches have emerged as promising candidates in the search for combining SAR and optical imagery. In addition, recent research has indicated that machine learning-based approaches have great potential for filling the information gap posed by utilizing only one sensor type in Earth observation applications. However, several challenges remain, and combining them is a multi-step process where no one-size-fits-all approach is available. This article reviews traditional, state-of-the-art, and recent development trends in SAR-optical co-registration methods.https://www.mdpi.com/2072-4292/15/3/850remote sensingSAR and optical registrationdeep learning |
| spellingShingle | Oscar Sommervold Michele Gazzea Reza Arghandeh A Survey on SAR and Optical Satellite Image Registration Remote Sensing remote sensing SAR and optical registration deep learning |
| title | A Survey on SAR and Optical Satellite Image Registration |
| title_full | A Survey on SAR and Optical Satellite Image Registration |
| title_fullStr | A Survey on SAR and Optical Satellite Image Registration |
| title_full_unstemmed | A Survey on SAR and Optical Satellite Image Registration |
| title_short | A Survey on SAR and Optical Satellite Image Registration |
| title_sort | survey on sar and optical satellite image registration |
| topic | remote sensing SAR and optical registration deep learning |
| url | https://www.mdpi.com/2072-4292/15/3/850 |
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