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首页> 外文期刊>International journal of remote sensing >Tiny moving vehicle detection in satellite video with constraints of multiple prior information
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Tiny moving vehicle detection in satellite video with constraints of multiple prior information

机译：微小的移动车辆检测在卫星视频中具有多个先前信息的约束

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摘要

ith the rapid development of remote sensing, satellite video has become an important data source for vehicle detection, which provides a broader field of surveillance. The achieved work generally focuses on aerial video with moderately sized objects based on feature extraction. However, the moving vehicles in satellite video imagery range from just a few pixels to dozens of pixels and exhibit low contrast with respect to the background, which makes it hard to get available appearance or shape information this paper, a tiny vehicle detection method based on spatio-temporal information is proposed to constrain the significance of the image. Firstly, the background modelling method is used to obtain the motion heat map of the image and constrain the motion region. A significance detection method for small targets was used to obtain the significance mapping of these regions. Finally, the detection results were optimized by combining the significance neighbourhood information and the time information between frames to output the binary target detection map. Finally, taking different urban road scenes in 'Jilin-1'satellite video as examples and compares a variety of existing algorithms. Experiments prove that the proposed algorithm can maintain false alarm rate of less than 10% when the detection accuracy and recall rate reach 85% and has certain anti-interference ability in the image environment with satellite Angle deviation.
机译：虽然遥感的快速发展，卫星视频已成为车辆检测的重要数据源，其提供更广泛的监视领域。实现的工作通常专注于基于特征提取的中等大小对象的空中视频。然而，卫星视频图像中的移动车辆从几十像素到几十个像素的范围，并且相对于背景呈现低对比度，这使得难以获得本文的出现或形状信息，这是一种基于的微小车辆检测方法提出了几种时间信息来限制图像的意义。首先，使用背景建模方法来获得图像的运动热图并限制运动区域。用于小靶的显着性检测方法来获得这些区域的重要性映射。最后，通过组合帧之间的意义邻域信息和时间信息来优化检测结果以输出二进制目标检测映射。最后，在“Jilin-1'Satellite”视频中以不同的城市道路场景为例，并比较各种现有算法。实验证明，当检测精度和召回率达到85％时，所提出的算法可以保持误报率小于10％，并且在具有卫星角度偏差的图像环境中具有某些抗干扰能力。

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  • 来源
    《International journal of remote sensing》 |2021年第12期|4110-4125|共16页
  • 作者

    Lei Junfeng; Dong Yuxuan; Sui Haigang;

  • 作者单位

    Wuhan Univ Sch Elect Informat Wuhan Peoples R China;

    Wuhan Univ Sch Elect Informat Wuhan Peoples R China;

    Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
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