Research on Infrared Small Target Detection Algorithm Based on Foreground Moving Target and Deep Learning for Space Detection

Addressing the challenging problem of detecting small targets in space, an infrared small target detection algorithm that incorporates foreground moving targets and deep learning is introduced. By running the foreground motion target detection algorithm and the deep learning YOLOv5 target detection algorithm, the regions where the motion target is located are obtained respectively. Then, the suspicious region of motion small targets is focused on and framed through region comparison. To verify the effectiveness of the algorithm, an infrared image dataset was constructed, and the experimental results demonstrate that the designed algorithm can effectively achieve intelligent detection of infrared small targets from kilometers away. This offers substantial support for practical applications in the fields of space exploration, deep space exploration, and security monitoring. It holds substantial application value for the integrated air and space monitoring and detection of small targets in space.

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Publication Details

Journal
Space Science & Technology
Published
2025-01-01
DOI
https://doi.org/10.34133/space.0216
Citations
2
Primary Topic
Infrared Target Detection Methodologies
Type
article
Field-Weighted Citation Impact
9.99
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Research on Infrared Small Target Detection Algorithm Based on Foreground Moving Target and Deep Learning for Space Detection

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article

Research on Infrared Small Target Detection Algorithm Based on Foreground Moving Target and Deep Learning for Space Detection

Xiang Gao, Dongming Cai, Sebastian Lang, Ziyuan Yang, Weidong Wang, Duk Kyung Kim, Dan Shan, Xiaofeng Wang
article en
2 citations

Abstract

Addressing the challenging problem of detecting small targets in space, an infrared small target detection algorithm that incorporates foreground moving targets and deep learning is introduced. By running the foreground motion target detection algorithm and the deep learning YOLOv5 target detection algorithm, the regions where the motion target is located are obtained respectively. Then, the suspicious region of motion small targets is focused on and framed through region comparison. To verify the effectiveness of the algorithm, an infrared image dataset was constructed, and the experimental results demonstrate that the designed algorithm can effectively achieve intelligent detection of infrared small targets from kilometers away. This offers substantial support for practical applications in the fields of space exploration, deep space exploration, and security monitoring. It holds substantial application value for the integrated air and space monitoring and detection of small targets in space.

Space Science & TechnologyVol. 5
Beijing Institute of Technology (CN), Inha University (KR), Shenyang Jianzhu University (CN)
Openalex Percentile: Top 3%
Infrared Target Detection Methodologies
9.99
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