| 背景差分与帧间差分相融合的遥感卫星视频运动车辆检测方法 |
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| 作者姓名： | 袁益琴 何国金 王桂周 江威 康金忠 |
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| 作者单位： | 1. 中国科学院遥感与数字地球研究所, 北京 100094;
2. 中国科学院大学, 北京 100049;
3. 海南省地球观测重点实验室, 海南 三亚 572000;
4. 吉林大学地球探测科学与技术学院, 长春 130012 |
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| 基金项目： | 国家重点研发计划全球变化及应对专项课题（2016YFA0600302），海南省重大科技计划项目（ZDKJ2016021，ZDKJ2016015-1）和中国科学院大学生创新实践训练计划（Y6Y01724KX）资助 |
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| 摘 要： | 遥感视频卫星的出现为实时连续对地观测提供了新的契机，为遥感动态监测与目标跟踪提供了新数据源。在分析遥感卫星视频目标检测与传统监控视频目标检测的差异的基础上，阐述现有目标检测算法直接应用到遥感卫星视频上存在的不足，提出一种背景差分与帧间差分相融合的方法并将其应用于遥感卫星视频运动车辆的目标检测中。通过抽取UrtheCast遥感卫星视频的4帧实验图像，分别采用背景差分法、帧间差分法和本文提出的方法对运动车辆进行检测并分析。结果表明，本文提出的方法能够更有效抑制移动的背景边缘和残留噪声干扰，提高检测的正确度和质量，在遥感卫星视频运动目标检测中具有良好的应用潜力。
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| 关 键 词： | 视频卫星 背景差分法 帧间差分法 目标检测 |
| 收稿时间： | 2017-03-04 |
| 修稿时间： | 2017-04-07 |
A background subtraction and frame subtraction combined method for moving vehicle detection in satellite video data |
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| Authors: | YUAN Yiqin HE Guojin WANG Guizhou JIANG Wei KANG Jinzhong |
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| Institution: | 1. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Key Laboratory for Earth Observation of Hainan Province, Sanya 572000, Hainan, China;
4. College of Earth Exploration Science and Technology, Jilin University, Changchun 130012, China |
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| Abstract: | Appearance of video satellite brings a new favorable opportunity for real-time observation of remote sensing and provides a kind of new data for dynamic monitoring and target tracking. Based on the differences in target detection between remote sensing satellite video and traditional surveillance video, this work indicates the problems about applying existing target detection algorithm directly to satellite video. A new approach which combines the background subtraction and frame subtraction technologies is proposed for better detection of the moving target in remote sensing satellite video. Moving vehicles in 4 frame images acquired from UrtheCast videos are detected by using the background subtraction method, the frame subtraction method, and the proposed method. The results indicate that the proposed method has a good ability in reducing the errors of mobile background edges and residual noises, improves the correctness and quality of detection, and has a promising application in moving target detection in satellite videos. |
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| Keywords: | video satellite background subtraction frame subtraction target detection |
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