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Complicated Background Suppression of ViSAR Image For Moving Target Shadow Detection

Authors :
Yang, Zhenyu
Zhang, Xiaoling
Zhan, Xu
Publication Year :
2022

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, 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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2209.10431
Document Type :
Working Paper
Full Text :
https://doi.org/10.1109/IGARSS46834.2022.9883465