论文标题
复杂的背景抑制Visar图像用于移动目标阴影检测
Complicated Background Suppression of ViSAR Image For Moving Target Shadow Detection
论文作者
论文摘要
现有的视频合成孔径雷达（Visar）移动目标阴影检测方法基于深神经网络大多会产生许多错误的警报和丢失的检测，因为前景背景的难度不佳。为了解决这个问题，我们提出了一种抑制Visar的复杂背景以进行目标检测的方法。在这项工作中，提出的方法用于抑制背景。然后，我们使用多个目标检测网络来检测移动目标阴影。实验结果表明，所提出的方法可以有效地抑制复杂的背景信息的干扰，并提高Visar中移动目标阴影检测的准确性。现有的视频合成孔径雷达（Visar）移动目标阴影检测方法基于深神经网络大多会产生许多错误的警报和丢失的检测，因为前景背景的难度不佳。为了解决这个问题，我们提出了一种抑制Visar的复杂背景以进行目标检测的方法。在这项工作中，提出的方法用于抑制背景。然后，我们使用多个目标检测网络来检测移动目标阴影。实验结果表明，所提出的方法可以有效地抑制复杂的背景信息的干扰，并提高Visar中移动目标阴影检测的准确性。
The existing Video Synthetic Aperture Radar (ViSAR) moving target shadow detection methods based on deep neural networks mostly generate numerous false alarms and missing detections, because of the foreground-background indistinguishability. To solve this problem, we propose a method to suppress complicated background of ViSAR for moving target detection. In this work, the proposed method is used to suppress background; then, we use several target detection networks to detect the moving target shadows. The experimental result shows that the proposed method can effectively suppress the interference of complicated back-ground information and improve the accuracy of moving target shadow detection in ViSAR. The existing Video Synthetic Aperture Radar (ViSAR) moving target shadow detection methods based on deep neural networks mostly generate numerous false alarms and missing detections, because of the foreground-background indistinguishability. To solve this problem, we propose a method to suppress complicated background of ViSAR for moving target detection. In this work, the proposed method is used to suppress background; then, we use several target detection networks to detect the moving target shadows. The experimental result shows that the proposed method can effectively suppress the interference of complicated back-ground information and improve the accuracy of moving target shadow detection in ViSAR.
