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一种基于多尺度点状目标建模的检测算法

Detection algorithm based on multi-scale spotted target modeling

  • 摘要: 为了解决点状小目标传统建模检测算法易受小目标自身暗淡呈点状的影响,在检测过程中小目标丢失或背景信息被误检成目标的问题,采用一种更加有效的多尺度点状小目标建模算法,对背景和可疑目标进行建模,得到了可疑目标图像。使用一种阈值分割算法,将真实目标从可疑目标中提取出来,进行了理论分析和实验验证。结果表明,该算法在同一数据集下,相对其它算法检测到点状小目标的轨迹更加接近真实轨迹。该研究对提高小目标检测效果的精度是有帮助的。

     

    Abstract: In order to solve the problem that the traditional modeling detection algorithm for spotted small target is susceptible to the dim and spotted targets, resulting in the loss of small target or the false detection that treat the background information as the target during the detection process, a more effective multi-scale spotted small target modeling algorithm was adopted. By modeling the background and suspicious target, the suspicious target image could be obtained. Finally, a threshold segmentation algorithm was used to extract the real target from the suspicious target, and then the theoretical analysis and experimental verification were carried out. The results show that under the same data set, the trajectory of small target dected by this algorithm is closer to the real trajectory than those by other algorithms. This research is helpful to improve the accuracy of small targets detection.

     

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