A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds
Human space exploration has brought a growing crowded operating environment for in-orbit spacecraft. Monitoring the space environment and detecting space targets with photoelectric equipment has extensive and realistic significance in space safety. In this study, a local spatial–temporal registratio...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/16/4/669 |
| _version_ | 1797297078709256192 |
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| author | Yueqi Su Xin Chen Chen Cang Fenghong Li Peng Rao |
| author_facet | Yueqi Su Xin Chen Chen Cang Fenghong Li Peng Rao |
| author_sort | Yueqi Su |
| collection | DOAJ |
| description | Human space exploration has brought a growing crowded operating environment for in-orbit spacecraft. Monitoring the space environment and detecting space targets with photoelectric equipment has extensive and realistic significance in space safety. In this study, a local spatial–temporal registration (LSTR) method is proposed to detect moving small targets in space. Firstly, we applied the local region registration to estimate the neighbor background motion model. Secondly, we analyzed the temporal local grayscale difference between the strong clutter and target region and measured the temporal local–central region difference to enhance the target. Then, the temporal pixel contrast map was calculated, which further retains the target signal and suppresses the residue clutter. Finally, a simple adaptive threshold segmentation algorithm was applied to the saliency map to segment the targets. Comparative experiments were conducted on four groups of image sequences to validate the efficiency and robustness of the algorithm. The experimental findings indicate that the proposed method performs well in target enhancement and clutter suppression under different scenarios. |
| first_indexed | 2024-03-07T22:16:04Z |
| format | Article |
| id | doaj.art-876a573480bb467fa713a34a233dce02 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-07T22:16:04Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-876a573480bb467fa713a34a233dce022024-02-23T15:33:02ZengMDPI AGRemote Sensing2072-42922024-02-0116466910.3390/rs16040669A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated BackgroundsYueqi Su0Xin Chen1Chen Cang2Fenghong Li3Peng Rao4Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaShanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaShanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaShanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaShanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 200083, ChinaHuman space exploration has brought a growing crowded operating environment for in-orbit spacecraft. Monitoring the space environment and detecting space targets with photoelectric equipment has extensive and realistic significance in space safety. In this study, a local spatial–temporal registration (LSTR) method is proposed to detect moving small targets in space. Firstly, we applied the local region registration to estimate the neighbor background motion model. Secondly, we analyzed the temporal local grayscale difference between the strong clutter and target region and measured the temporal local–central region difference to enhance the target. Then, the temporal pixel contrast map was calculated, which further retains the target signal and suppresses the residue clutter. Finally, a simple adaptive threshold segmentation algorithm was applied to the saliency map to segment the targets. Comparative experiments were conducted on four groups of image sequences to validate the efficiency and robustness of the algorithm. The experimental findings indicate that the proposed method performs well in target enhancement and clutter suppression under different scenarios.https://www.mdpi.com/2072-4292/16/4/669space target detectionimage sequencesspatial–temporal domaininterframe registration |
| spellingShingle | Yueqi Su Xin Chen Chen Cang Fenghong Li Peng Rao A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds Remote Sensing space target detection image sequences spatial–temporal domain interframe registration |
| title | A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds |
| title_full | A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds |
| title_fullStr | A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds |
| title_full_unstemmed | A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds |
| title_short | A Space Target Detection Method Based on Spatial–Temporal Local Registration in Complicated Backgrounds |
| title_sort | space target detection method based on spatial temporal local registration in complicated backgrounds |
| topic | space target detection image sequences spatial–temporal domain interframe registration |
| url | https://www.mdpi.com/2072-4292/16/4/669 |
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