TY - GEN
T1 - A Ship Wake Detection Method in SAR Images Based on Joint Sparse Representation
AU - Xu, Huaping
AU - Xiao, Shuangying
AU - Guan, Yanan
AU - Li, Wei
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - The strong sea clutter and noise in synthetic aperture radar (SAR) images will cover weak ship wakes, making it difficult for conventional ship wake detection methods to accurately detect ship wakes. A ship wake detection method based on joint sparse representation is proposed in this paper to improve the detection effect of ship wakes in complex backgrounds. Firstly, the sparse representation model of SAR images based on the Radon transform is constructed. Secondly, using dual-domain images in the spatial and gradient domains, the optimization function for ship wake detection based on joint sparse representation is constructed and solved iteratively. Then, the weighted clustering criterion based on sparse coefficient and Radon coordinates is used to perform sparse coefficient clustering, and the centerline detection of the ship wake is realized by the inverse Radon transformation of the cluster center. Finally, the experimental results of TerraSAR-X images are used to verify the effectiveness of the proposed method.
AB - The strong sea clutter and noise in synthetic aperture radar (SAR) images will cover weak ship wakes, making it difficult for conventional ship wake detection methods to accurately detect ship wakes. A ship wake detection method based on joint sparse representation is proposed in this paper to improve the detection effect of ship wakes in complex backgrounds. Firstly, the sparse representation model of SAR images based on the Radon transform is constructed. Secondly, using dual-domain images in the spatial and gradient domains, the optimization function for ship wake detection based on joint sparse representation is constructed and solved iteratively. Then, the weighted clustering criterion based on sparse coefficient and Radon coordinates is used to perform sparse coefficient clustering, and the centerline detection of the ship wake is realized by the inverse Radon transformation of the cluster center. Finally, the experimental results of TerraSAR-X images are used to verify the effectiveness of the proposed method.
KW - Radon transform
KW - SAR images
KW - ship wake detection
KW - sparse representation
UR - https://www.scopus.com/pages/publications/85208455863
U2 - 10.1109/IGARSS53475.2024.10642367
DO - 10.1109/IGARSS53475.2024.10642367
M3 - 会议稿件
AN - SCOPUS:85208455863
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 9879
EP - 9882
BT - IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2024
Y2 - 7 July 2024 through 12 July 2024
ER -