Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained Detection
The detection of vehicle targets in wide-area Synthetic Aperture Radar (SAR) images is crucial for real-time reconnaissance tasks and the widespread application of remote sensing technology in military and civilian fields. However, existing detection methods often face difficulties in handling large...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/15/13/3242 |
| _version_ | 1797590900396785664 |
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| author | Yucheng Song Shuo Wang Qing Li Hongbin Mu Ruyi Feng Tian Tian Jinwen Tian |
| author_facet | Yucheng Song Shuo Wang Qing Li Hongbin Mu Ruyi Feng Tian Tian Jinwen Tian |
| author_sort | Yucheng Song |
| collection | DOAJ |
| description | The detection of vehicle targets in wide-area Synthetic Aperture Radar (SAR) images is crucial for real-time reconnaissance tasks and the widespread application of remote sensing technology in military and civilian fields. However, existing detection methods often face difficulties in handling large-scale images and achieving high accuracy. In this study, we address the challenges of detecting vehicle targets in wide-area SAR images and propose a novel method that combines coarse-grained judgment with fine-grained detection to overcome these challenges. Our proposed vehicle detection model is based on YOLOv5, featuring a CAM attention module, CAM-FPN network, and decoupled detection head, and it is strengthened with background-assisted supervision and coarse-grained judgment. These various techniques not only improve the accuracy of the detection algorithms, but also enhance SAR image processing speed. We evaluate the performance of our model using the Wide-area SAR Vehicle Detection (WSVD) dataset. The results demonstrate that the proposed method achieves a high level of accuracy in identifying vehicle targets in wide-area SAR images. Our method effectively addresses the challenges of detecting vehicle targets in wide-area SAR images, and has the potential to significantly enhance real-time reconnaissance tasks and promote the widespread application of remote sensing technology in various fields. |
| first_indexed | 2024-03-11T01:30:06Z |
| format | Article |
| id | doaj.art-2d3f493bbb72450eb4fc2c8df2ddffd1 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T01:30:06Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-2d3f493bbb72450eb4fc2c8df2ddffd12023-11-18T17:23:24ZengMDPI AGRemote Sensing2072-42922023-06-011513324210.3390/rs15133242Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained DetectionYucheng Song0Shuo Wang1Qing Li2Hongbin Mu3Ruyi Feng4Tian Tian5Jinwen Tian6School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, ChinaBeijing Institute of Astronautical Systems Engineering, Beijing 100076, ChinaSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, ChinaBeijing Institute of Astronautical Systems Engineering, Beijing 100076, ChinaSchool of Computer Science, China University of Geosciences, Wuhan 430074, ChinaSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, ChinaSchool of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, ChinaThe detection of vehicle targets in wide-area Synthetic Aperture Radar (SAR) images is crucial for real-time reconnaissance tasks and the widespread application of remote sensing technology in military and civilian fields. However, existing detection methods often face difficulties in handling large-scale images and achieving high accuracy. In this study, we address the challenges of detecting vehicle targets in wide-area SAR images and propose a novel method that combines coarse-grained judgment with fine-grained detection to overcome these challenges. Our proposed vehicle detection model is based on YOLOv5, featuring a CAM attention module, CAM-FPN network, and decoupled detection head, and it is strengthened with background-assisted supervision and coarse-grained judgment. These various techniques not only improve the accuracy of the detection algorithms, but also enhance SAR image processing speed. We evaluate the performance of our model using the Wide-area SAR Vehicle Detection (WSVD) dataset. The results demonstrate that the proposed method achieves a high level of accuracy in identifying vehicle targets in wide-area SAR images. Our method effectively addresses the challenges of detecting vehicle targets in wide-area SAR images, and has the potential to significantly enhance real-time reconnaissance tasks and promote the widespread application of remote sensing technology in various fields.https://www.mdpi.com/2072-4292/15/13/3242vehicle detectionSAR imageryremote sensing images |
| spellingShingle | Yucheng Song Shuo Wang Qing Li Hongbin Mu Ruyi Feng Tian Tian Jinwen Tian Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained Detection Remote Sensing vehicle detection SAR imagery remote sensing images |
| title | Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained Detection |
| title_full | Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained Detection |
| title_fullStr | Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained Detection |
| title_full_unstemmed | Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained Detection |
| title_short | Vehicle Target Detection Method for Wide-Area SAR Images Based on Coarse-Grained Judgment and Fine-Grained Detection |
| title_sort | vehicle target detection method for wide area sar images based on coarse grained judgment and fine grained detection |
| topic | vehicle detection SAR imagery remote sensing images |
| url | https://www.mdpi.com/2072-4292/15/13/3242 |
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