SAR ship detection based on salience region extraction and multi-branch attention
Ship detection of synthetic aperture radar (SAR) images has received much attention in the field of military and people's livelihood. The radar pulse signals reflected by buildings and sea clutter would reduce the salience of ships in images, making ship features blurrier. This leads to interfe...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223003138 |
| _version_ | 1797677696525795328 |
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| author | Cheng Zha Weidong Min Qing Han Xin Xiong Qi Wang Hongyue Xiang |
| author_facet | Cheng Zha Weidong Min Qing Han Xin Xiong Qi Wang Hongyue Xiang |
| author_sort | Cheng Zha |
| collection | DOAJ |
| description | Ship detection of synthetic aperture radar (SAR) images has received much attention in the field of military and people's livelihood. The radar pulse signals reflected by buildings and sea clutter would reduce the salience of ships in images, making ship features blurrier. This leads to interference and erroneous judgments in SAR ship detection. To solve this problem, a novel SAR ship detection method based on salience region extraction (SRE) and multi-branch attention (MBA) is proposed in this paper. The designed SRE module extracts all regions where ships may exist according to the maximum inter-class variance, and filters out irrelevant background information. Then, the proposed MBA module is used to enhance the expressive ability of ship features, so as to improve the salience of the ship features. Extensive comparison experiments have been conducted to prove the effectiveness of SRE and MBA modules. The average precision (AP0.5) is increased by 3.20% and 2.13% through SRE module and MBA module, respectively. The proposed method could achieve 0.8966 and 0.9697 in AP0.5for inshore and offshore scenes, which gives the best results. |
| first_indexed | 2024-03-11T22:48:58Z |
| format | Article |
| id | doaj.art-a4c3b3dbec654330887e13584c83ed30 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-11T22:48:58Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-a4c3b3dbec654330887e13584c83ed302023-09-22T04:38:22ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-09-01123103489SAR ship detection based on salience region extraction and multi-branch attentionCheng Zha0Weidong Min1Qing Han2Xin Xiong3Qi Wang4Hongyue Xiang5School of Mathematics and Computer Science, Nanchang University, Nanchang 330031, ChinaSchool of Mathematics and Computer Science, Nanchang University, Nanchang 330031, China; Institute of Metaverse, Nanchang University, Nanchang 330031, China; Jiangxi Key Laboratory of Smart City, Nanchang 330031, China; Corresponding author at: School of Mathematics and Computer Science, Nanchang University, Nanchang 330031, China.School of Mathematics and Computer Science, Nanchang University, Nanchang 330031, China; Institute of Metaverse, Nanchang University, Nanchang 330031, China; Jiangxi Key Laboratory of Smart City, Nanchang 330031, ChinaInstitute of Metaverse, Nanchang University, Nanchang 330031, China; Information Department, First Affiliated Hospital of Nanchang University, Nanchang 330006, ChinaSchool of Mathematics and Computer Science, Nanchang University, Nanchang 330031, China; Institute of Metaverse, Nanchang University, Nanchang 330031, China; Jiangxi Key Laboratory of Smart City, Nanchang 330031, ChinaSchool of Mathematics and Computer Science, Nanchang University, Nanchang 330031, ChinaShip detection of synthetic aperture radar (SAR) images has received much attention in the field of military and people's livelihood. The radar pulse signals reflected by buildings and sea clutter would reduce the salience of ships in images, making ship features blurrier. This leads to interference and erroneous judgments in SAR ship detection. To solve this problem, a novel SAR ship detection method based on salience region extraction (SRE) and multi-branch attention (MBA) is proposed in this paper. The designed SRE module extracts all regions where ships may exist according to the maximum inter-class variance, and filters out irrelevant background information. Then, the proposed MBA module is used to enhance the expressive ability of ship features, so as to improve the salience of the ship features. Extensive comparison experiments have been conducted to prove the effectiveness of SRE and MBA modules. The average precision (AP0.5) is increased by 3.20% and 2.13% through SRE module and MBA module, respectively. The proposed method could achieve 0.8966 and 0.9697 in AP0.5for inshore and offshore scenes, which gives the best results.http://www.sciencedirect.com/science/article/pii/S1569843223003138Synthetic aperture radarShip detectionSalience region extractionMulti-branch attention |
| spellingShingle | Cheng Zha Weidong Min Qing Han Xin Xiong Qi Wang Hongyue Xiang SAR ship detection based on salience region extraction and multi-branch attention International Journal of Applied Earth Observations and Geoinformation Synthetic aperture radar Ship detection Salience region extraction Multi-branch attention |
| title | SAR ship detection based on salience region extraction and multi-branch attention |
| title_full | SAR ship detection based on salience region extraction and multi-branch attention |
| title_fullStr | SAR ship detection based on salience region extraction and multi-branch attention |
| title_full_unstemmed | SAR ship detection based on salience region extraction and multi-branch attention |
| title_short | SAR ship detection based on salience region extraction and multi-branch attention |
| title_sort | sar ship detection based on salience region extraction and multi branch attention |
| topic | Synthetic aperture radar Ship detection Salience region extraction Multi-branch attention |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223003138 |
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