Visible and Infrared Image Fusion-Based Image Quality Enhancement with Applications to Space Debris On-Orbit Surveillance
The increasing amount of space debris in recent years has greatly threatened space operation. In order to ensure the safety level of spacecraft, space debris perception via on-orbit visual sensors has become a promising solution. However, the perception capability of visual sensors largely depends o...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Aerospace Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/6300437 |
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| _version_ | 1832549029641191424 |
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| author | Jiang Tao Yunfeng Cao Meng Ding Zhouyu Zhang |
| author_facet | Jiang Tao Yunfeng Cao Meng Ding Zhouyu Zhang |
| author_sort | Jiang Tao |
| collection | DOAJ |
| description | The increasing amount of space debris in recent years has greatly threatened space operation. In order to ensure the safety level of spacecraft, space debris perception via on-orbit visual sensors has become a promising solution. However, the perception capability of visual sensors largely depends on illumination, which tends to be insufficient in dark environments. Since the images captured by visible and infrared sensors are highly complementary in dark environments, a convolutional sparse representation-based visible and infrared image fusion algorithm is proposed in this paper to expand the applicability of visual sensors. In particular, the local contrast measure is applied to obtain the refined weight map for fusing the base layers, which is more robust in a dark space environment. The algorithm can settle two significant problems in space debris surveillance, namely, improving the signal-noise ratio in a noise space environment and preserving more detailed information in a dark space environment. A space debris dataset containing registered visible and infrared images has been purposely created and used for algorithm evaluation. Experimental results demonstrate that the proposed method in this paper is effective for enhancing image qualities and can achieve favorable effects compared to other state-of-the-art algorithms. |
| format | Article |
| id | doaj-art-5bea9784d1714817b2ba1e4fa19061fb |
| institution | Kabale University |
| issn | 1687-5974 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Aerospace Engineering |
| spelling | doaj-art-5bea9784d1714817b2ba1e4fa19061fb2025-02-03T06:12:24ZengWileyInternational Journal of Aerospace Engineering1687-59742022-01-01202210.1155/2022/6300437Visible and Infrared Image Fusion-Based Image Quality Enhancement with Applications to Space Debris On-Orbit SurveillanceJiang Tao0Yunfeng Cao1Meng Ding2Zhouyu Zhang3College of AstronauticsCollege of AstronauticsCollege of Civil AviationCollege of AstronauticsThe increasing amount of space debris in recent years has greatly threatened space operation. In order to ensure the safety level of spacecraft, space debris perception via on-orbit visual sensors has become a promising solution. However, the perception capability of visual sensors largely depends on illumination, which tends to be insufficient in dark environments. Since the images captured by visible and infrared sensors are highly complementary in dark environments, a convolutional sparse representation-based visible and infrared image fusion algorithm is proposed in this paper to expand the applicability of visual sensors. In particular, the local contrast measure is applied to obtain the refined weight map for fusing the base layers, which is more robust in a dark space environment. The algorithm can settle two significant problems in space debris surveillance, namely, improving the signal-noise ratio in a noise space environment and preserving more detailed information in a dark space environment. A space debris dataset containing registered visible and infrared images has been purposely created and used for algorithm evaluation. Experimental results demonstrate that the proposed method in this paper is effective for enhancing image qualities and can achieve favorable effects compared to other state-of-the-art algorithms.http://dx.doi.org/10.1155/2022/6300437 |
| spellingShingle | Jiang Tao Yunfeng Cao Meng Ding Zhouyu Zhang Visible and Infrared Image Fusion-Based Image Quality Enhancement with Applications to Space Debris On-Orbit Surveillance International Journal of Aerospace Engineering |
| title | Visible and Infrared Image Fusion-Based Image Quality Enhancement with Applications to Space Debris On-Orbit Surveillance |
| title_full | Visible and Infrared Image Fusion-Based Image Quality Enhancement with Applications to Space Debris On-Orbit Surveillance |
| title_fullStr | Visible and Infrared Image Fusion-Based Image Quality Enhancement with Applications to Space Debris On-Orbit Surveillance |
| title_full_unstemmed | Visible and Infrared Image Fusion-Based Image Quality Enhancement with Applications to Space Debris On-Orbit Surveillance |
| title_short | Visible and Infrared Image Fusion-Based Image Quality Enhancement with Applications to Space Debris On-Orbit Surveillance |
| title_sort | visible and infrared image fusion based image quality enhancement with applications to space debris on orbit surveillance |
| url | http://dx.doi.org/10.1155/2022/6300437 |
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