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

作　　者：YAN Congqiang GUO Zhengyun CAI Yunze 鄢丛强;郭正玉;蔡云泽(Department of Automation,Shanghai Jiao Tong University,Shanghai,200240,China;Key Laboratory of System Control and Information Processing of Ministry of Education,Shanghai,200240,China;China Airborne Missile Academy,Luoyang,471009,Henan,China;National Key Laboratory of Air-Based Information Perception and Fusion,Luoyang,471000,Henan,China)

机构地区：[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

出　　处：《Journal of Shanghai Jiaotong university(Science)》2024年第4期702-711,共10页上海交通大学学报（英文版）

基　　金：Industry-University-Research Cooperation Fund Project of the Eighth Research Institute of China Aerospace Science and Technology Corporation(No.USCAST2021-5);Aeronautical Science Foundation of China(No.20220001057001)。

摘　　要：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.

关 键 词：synthetic aperture radar(SAR) ship wake data augmentation cycle-consistent generative adversarial network(CycleGAN) attention mechanism 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]