Merchant ship classification in high-resolution SAR image based on joint superstructure scattering features

ABSTRACT

Ship classification has long been a challenging task in synthetic aperture radar (SAR) applications. With the improvement of SAR resolution, it has gradually become possible based on high-resolution SAR images. This letter presents a joint feature representation method for characterizing the superstructure scattering features of merchant ships, and then a hierarchical scheme for classifying merchant ships in high-resolution SAR images based on integrated macro and detailed superstructure features is proposed. Comprehensive experiment on three types of high-resolution SAR samples demonstrates that the proposed features and method have the ability to improve the performance of merchant ship classification in SAR images.

KEYWORDS:

• Synthetic aperture radar (SAR)
• high-resolution
• ship classification
• chattering feature
• superstructure feature
• minimum enclosing rectangle
• macro feature
• detailed feature

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Xiaolong Wang

Xiaolong Wang, currently working in the Aerospace Information Research Institute, CAS, is an associate researcher. His research interests include SAR ground system construction, SAR image processing, intelligent target detection and classification, etc.

Chang Liu

Chang Liu, currently working in the Aerospace Information Research Institute, CAS, is a researcher. His research interests include airborne SAR system design, SAR signal processing, intelligent SAR image processing, etc.

Zhiyong Li

Zhiyong Li, currently working in the Aerospace Information Research Institute, CAS, is an assistant researcher. His research interests include geographic information system, SAR image processing, GIS software design, etc.

Xin Zhang

Xin Zhang, currently working in the Aerospace Information Research Institute, CAS, is an assistant researcher. Her research interests include geographic information system and SAR image processing.

Xubing Dong

Xubing Dong, currently working in the Aerospace Information Research Institute, CAS, is an assistant researcher. His research interests include deep learning and intelligent SAR image processing.