| Autor: |
Qu, Haicheng, Li, Ruike, Shan, Yimeng, Wang, Meng |
| Zdroj: |
Signal, Image & Video Processing; Mar2024, Vol. 18 Issue 2, p1763-1777, 15p |
| Abstrakt: |
Synthetic aperture radar (SAR) images are widely used for maritime surveillance due to their all-weather imaging capability and day–night visibility. However, the sparsity of offshore scene targets and the interference of land facilities in inshore scenes increase the difficulty of SAR ship detection, and the anchor-based detection algorithms require a large amount of computational resources. Therefore, this paper proposes an anchor-free detection method for SAR ship detection based on spatial feature enhancement and weight-guided fusion, called SW-Net. First, a spatial feature enhancement module is constructed to reduce the information loss caused by a sudden decrease in the number of feature channels by enhancing the spatial structural information of the features. Additionally, to solve the problem of blurred target boundaries after fusing features of different scales, a weight-guided fusion module is designed to use high-level features to generate weight vectors to guide the fusion of low-level features and generate more powerful semantic information. Finally, the complete intersection over union loss function is utilized to optimize the predicted boxes, to increase their quality. We performed experiments on the SSDD and HRSID public datasets to evaluate SW-Net's performance. The results of our experiments show that SW-Net consistently surpasses existing methods as a matter of detection accuracy, demonstrating the efficacy of our suggested approach. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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