Remote Sensing Image Super-Resolution for the Visual System of a Flight Simulator: Dataset and Baseline
High-resolution remote sensing images are the key data source for the visual system of a flight simulator for training a qualified pilot. However, due to hardware limitations, it is an expensive task to collect spectral and spatial images at very high resolutions. In this work, we try to tackle this...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-03-01
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| Series: | Aerospace |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2226-4310/8/3/76 |
| _version_ | 1797541298325946368 |
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| author | Wenyi Ge Zhitao Wang Guigui Wang Shihan Tan Jianwei Zhang |
| author_facet | Wenyi Ge Zhitao Wang Guigui Wang Shihan Tan Jianwei Zhang |
| author_sort | Wenyi Ge |
| collection | DOAJ |
| description | High-resolution remote sensing images are the key data source for the visual system of a flight simulator for training a qualified pilot. However, due to hardware limitations, it is an expensive task to collect spectral and spatial images at very high resolutions. In this work, we try to tackle this issue with another perspective based on image super-resolution (SR) technology. First, we present a new ultra-high-resolution remote sensing image dataset named Airport80, which is captured from the airspace near various airports. Second, a deep learning baseline is proposed by applying the generative and adversarial mechanism, which is able to reconstruct a high-resolution image during a single image super-resolution. Experimental results for our benchmark demonstrate the effectiveness of the proposed network and show it has reached satisfactory performances. |
| first_indexed | 2024-03-10T13:13:58Z |
| format | Article |
| id | doaj.art-e5587eab169f4c80b3216bc2c6094e79 |
| institution | Directory Open Access Journal |
| issn | 2226-4310 |
| language | English |
| last_indexed | 2024-03-10T13:13:58Z |
| publishDate | 2021-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Aerospace |
| spelling | doaj.art-e5587eab169f4c80b3216bc2c6094e792023-11-21T10:35:16ZengMDPI AGAerospace2226-43102021-03-01837610.3390/aerospace8030076Remote Sensing Image Super-Resolution for the Visual System of a Flight Simulator: Dataset and BaselineWenyi Ge0Zhitao Wang1Guigui Wang2Shihan Tan3Jianwei Zhang4National Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, Chengdu 610000, ChinaBeijing Satellite Navigation Center (BSNC), Beijing 100094, ChinaNational Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, Chengdu 610000, ChinaNational Key Laboratory of Fundamental Science on Synthetic Vision, College of Computer Science, Sichuan University, Chengdu 610000, ChinaCollege of Computer Science, Sichuan University, Chengdu 610000, ChinaHigh-resolution remote sensing images are the key data source for the visual system of a flight simulator for training a qualified pilot. However, due to hardware limitations, it is an expensive task to collect spectral and spatial images at very high resolutions. In this work, we try to tackle this issue with another perspective based on image super-resolution (SR) technology. First, we present a new ultra-high-resolution remote sensing image dataset named Airport80, which is captured from the airspace near various airports. Second, a deep learning baseline is proposed by applying the generative and adversarial mechanism, which is able to reconstruct a high-resolution image during a single image super-resolution. Experimental results for our benchmark demonstrate the effectiveness of the proposed network and show it has reached satisfactory performances.https://www.mdpi.com/2226-4310/8/3/76flight simulatorremote sensing imagesuper-resolutiongenerative adversarial network |
| spellingShingle | Wenyi Ge Zhitao Wang Guigui Wang Shihan Tan Jianwei Zhang Remote Sensing Image Super-Resolution for the Visual System of a Flight Simulator: Dataset and Baseline Aerospace flight simulator remote sensing image super-resolution generative adversarial network |
| title | Remote Sensing Image Super-Resolution for the Visual System of a Flight Simulator: Dataset and Baseline |
| title_full | Remote Sensing Image Super-Resolution for the Visual System of a Flight Simulator: Dataset and Baseline |
| title_fullStr | Remote Sensing Image Super-Resolution for the Visual System of a Flight Simulator: Dataset and Baseline |
| title_full_unstemmed | Remote Sensing Image Super-Resolution for the Visual System of a Flight Simulator: Dataset and Baseline |
| title_short | Remote Sensing Image Super-Resolution for the Visual System of a Flight Simulator: Dataset and Baseline |
| title_sort | remote sensing image super resolution for the visual system of a flight simulator dataset and baseline |
| topic | flight simulator remote sensing image super-resolution generative adversarial network |
| url | https://www.mdpi.com/2226-4310/8/3/76 |
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