光电子快报(英文版), 2019, 15 (5): 391, Published Online: Jan. 7, 2020  

High resolution remote sensing image ship target detection technology based on deep learning

Author Affiliations
1 The 54th Research Institute of China Electronics Technology Group Corporation, Shijiazhuang 050081, China
2 CETC Key Laboratory of Aerospace Information Applications, Shijiazhuang 050081, China
3 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University,Wuhan 430079, China
Abstract
With the development of China's high-resolution special projects and the rapid development of commercial satellite, the resolution of the mainstream satellite remote sensing images has reached the sub-meter level. Ship target detection in high-resolution remote sensing images has always been the focus and hotspot in image understanding. Real-time and effective detection of ships play an extremely important role in marine transportation, military operations and so on. Firstly, the full-factor ship target sample library of high-resolution image is synthetically prepared. Then, based on the Faster R-CNN framework and Resnet model, optimize the parameters of the model to achieve accurate results. The simulation results show that the detection model trained in this paper has the highest recall rate of 98.01% and false alarm rate of 0.83%. It can be applied to the practical application of ship detection in remote sensing images.

WANG Min, CHEN Jin-yong, WANG Gang, GAO Feng, SUN Kang, XU Miao-zhong. High resolution remote sensing image ship target detection technology based on deep learning[J]. 光电子快报(英文版), 2019, 15(5): 391.

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