Complicated Background Suppression of ViSAR Image For Moving Target Shadow Detection
Zhenyu Yang, Xiaoling Zhang, Xu Zhan

TL;DR
This paper introduces a background suppression technique for ViSAR images that enhances moving target shadow detection accuracy by reducing false alarms caused by complex backgrounds.
Contribution
The paper presents a novel background suppression method for ViSAR images that improves moving target shadow detection accuracy over existing neural network approaches.
Findings
Effective suppression of background interference in ViSAR images.
Improved accuracy in moving target shadow detection.
Reduction in false alarms and missed detections.
Abstract
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,…
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Taxonomy
TopicsAdvanced SAR Imaging Techniques
