Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning
Synthetic Aperture Radar (SAR) is an indispensable remote sensing technology nowadays. However, due to the different imaging theory applied in Synthetic Aperture Radars, the interpretation of SAR images may come out as extremely different from conventional optical satellite images. Thus, to tackl...
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| Other Authors: | |
| Format: | Thesis-Master by Coursework |
| Language: | English |
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Nanyang Technological University
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/154639 |
| _version_ | 1826125018645397504 |
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| author | Zhou, Hao |
| author2 | Lu Yilong |
| author_facet | Lu Yilong Zhou, Hao |
| author_sort | Zhou, Hao |
| collection | NTU |
| description | Synthetic Aperture Radar (SAR) is an indispensable remote sensing technology
nowadays. However, due to the different imaging theory applied in Synthetic
Aperture Radars, the interpretation of SAR images may come out as extremely
different from conventional optical satellite images. Thus, to tackle with the
interpretation problem, a specialized SAR-optical image translation model is developed to directly translate the original SAR images into equivalent optical
satellite images. This model is implemented with a novel two-step Generative Adversarial Network architecture. To present the performance of proposed
model on SAR-Optical image translation task, remote sensing data acquired
from Sentinel-1 and Sentinel-2 is utilized for the model training and validation
phase. The final results indicate a promising performance both on enhancing
the human perception of translated optical images and increasing the statistical indices of PNSR and SSIM, which have reached at 19.09 dB and 0.4211
respectively. |
| first_indexed | 2024-10-01T06:29:52Z |
| format | Thesis-Master by Coursework |
| id | ntu-10356/154639 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:29:52Z |
| publishDate | 2022 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1546392023-07-04T17:43:06Z Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning Zhou, Hao Lu Yilong School of Electrical and Electronic Engineering EYLU@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Electrical and electronic engineering Synthetic Aperture Radar (SAR) is an indispensable remote sensing technology nowadays. However, due to the different imaging theory applied in Synthetic Aperture Radars, the interpretation of SAR images may come out as extremely different from conventional optical satellite images. Thus, to tackle with the interpretation problem, a specialized SAR-optical image translation model is developed to directly translate the original SAR images into equivalent optical satellite images. This model is implemented with a novel two-step Generative Adversarial Network architecture. To present the performance of proposed model on SAR-Optical image translation task, remote sensing data acquired from Sentinel-1 and Sentinel-2 is utilized for the model training and validation phase. The final results indicate a promising performance both on enhancing the human perception of translated optical images and increasing the statistical indices of PNSR and SSIM, which have reached at 19.09 dB and 0.4211 respectively. Master of Science (Signal Processing) 2022-01-03T07:04:03Z 2022-01-03T07:04:03Z 2021 Thesis-Master by Coursework Zhou, H. (2021). Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/154639 https://hdl.handle.net/10356/154639 en ISM-DISS-02473 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Electrical and electronic engineering Zhou, Hao Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning |
| title | Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning |
| title_full | Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning |
| title_fullStr | Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning |
| title_full_unstemmed | Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning |
| title_short | Cloud removal in optical remote sensing imagery based on direct translation from SAR to optical image using deep learning |
| title_sort | cloud removal in optical remote sensing imagery based on direct translation from sar to optical image using deep learning |
| topic | Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Engineering::Electrical and electronic engineering |
| url | https://hdl.handle.net/10356/154639 |
| work_keys_str_mv | AT zhouhao cloudremovalinopticalremotesensingimagerybasedondirecttranslationfromsartoopticalimageusingdeeplearning |