J Shanghai Jiaotong Univ Sci

Journal of Shanghai Jiaotong University(Science) >

2024 , Vol. 29 >Issue 4: 702 - 711

DOI: https://doi.org/10.1007/s12204-024-2746-8

Special Issue on Multi-Agent Collaborative Perception and Control

Data Augmentation of Ship Wakes in SAR Images Based on Improved CycleGAN

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  • (1. Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China; 2. Key Laboratory of System Control and Information Processing of Ministry of Education, Shanghai 200240, China; 3. China Airborne Missile Academy, Luoyang 471009, Henan, China; 4. National Key Laboratory of Air-Based Information Perception and Fusion, Luoyang 471000, Henan, China)

Accepted date: 2023-09-26

  Online published: 2024-07-28

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Abstract

The study on ship wakes of synthetic aperture radar (SAR) images holds great importance in detecting ship targets in the ocean. In this study, we focus on the issues of low quantity and insufficient diversity in ship wakes of SAR images, and propose a method of data augmentation of ship wakes in SAR images based on the improved cycle-consistent generative adversarial network (CycleGAN). The improvement measures mainly include two aspects: First, to enhance the quality of the generated images and guarantee a stable training process of the model, the least-squares loss is employed as the adversarial loss function; Second, the decoder of the generator is augmented with the convolutional block attention module (CBAM) to address the issue of missing details in the generated ship wakes of SAR images at the microscopic level. The experiment findings indicate that the improved CycleGAN model generates clearer ship wakes of SAR images, and outperforms the traditional CycleGAN models in both subjective and objective aspects.

Key words： synthetic aperture radar (SAR), ship wake, data augmentation, cycle-consistent generative adversarial network (CycleGAN), attention mechanism

Cite this article

YAN Congqiang1,2 (鄢丛强), GUO Zhengyun3,4 (郭正玉), CAI Yunze1,2∗∗ (蔡云泽) . Data Augmentation of Ship Wakes in SAR Images Based on Improved CycleGAN[J]. Journal of Shanghai Jiaotong University(Science), 2024 , 29(4) : 702 -711 . DOI: 10.1007/s12204-024-2746-8

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