A High Autonomous Sea Front Detection Algorithm Based on SAR Data

Authors

  • Su-qin Xu Navy Submarine Academy, Qingdao 266199, China
  • Hao Jiang Navy Submarine Academy, Qingdao 266199, China; CSSC Ocean Exploration Technology Institute Co., Ltd, Wuxi 214028, China
  • Ting-ting Li Navy Submarine Academy, Qingdao 266199, China
  • Li-ming Yuan Navy Submarine Academy, Qingdao 266199, China; CSSC Ocean Exploration Technology Institute Co., Ltd, Wuxi 214028, China
  • Lu Yu Navy Submarine Academy, Qingdao 266199, China
  • Jie Chen Navy Submarine Academy, Qingdao 266199, China
  • Biao Chen Navy Submarine Academy, Qingdao 266199, China
  • Bao-qiang Zhang Navy Submarine Academy, Qingdao 266199, China; CSSC Ocean Exploration Technology Institute Co., Ltd, Wuxi 214028, China

DOI:

https://doi.org/10.13052/jwe1540-9589.20211

Keywords:

Sea front, SAR, high autonomy, graphic detection

Abstract

This paper has proposed a high autonomous sea front detection algorithm based on SAR data. Through the innovative introduction of empirical mode decomposition method, a good image de-trend and de-stripe effect is achieved. By introducing the calculation of the maximum interclass variance, the automatic conversion of binary images is realized; through the use of polynomial fitting method, the independent screening of front information is realized, and the continuity of front detection results is improved. After comparison, it is found that the new algorithm proposed in this paper has greatly improved detection accuracy and autonomy compared with the old algorithm. Finally, a SAR data of the GF-3 satellite on the west side of Taiwan Island is used to test the new algorithm proposed in this paper. The results show that the detection results are highly consistent with the original image in morphology, and the changes in frontal intensity are also very detailed, verifying the accuracy and autonomy of the new method.

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Author Biographies

Su-qin Xu, Navy Submarine Academy, Qingdao 266199, China

Su-qin Xu, professor. Graduated from the University of Information Engineering with a master’s degree in engineering, and now teaches in the Naval Submarine Academy. She has been engaged in the research of marine remote sensing in the application field for a long time. She has undertaken a number of scientific research projects and made outstanding achievements in marine environment remote sensing, and has published more than 40 academic papers.

Hao Jiang, Navy Submarine Academy, Qingdao 266199, China; CSSC Ocean Exploration Technology Institute Co., Ltd, Wuxi 214028, China

Hao Jiang graduated from Shanghai Ocean University, majoring in marine technology. After that, he entered the ocean College of Zhejiang University and obtained his master’s degree, majoring in physical oceanography. He worked as a research assistant in Zhejiang University for a period of time, and now works as a research and Development Engineer in CSSC Ocean Exploration Technology Institute Co., Ltd. During his study and work, he participated in a large number of marine scientific research work, and conducted in-depth research in the field of ocean mesoscale and small-scale phenomena and the exchange of material and energy between ocean and atmosphere.

Ting-ting Li, Navy Submarine Academy, Qingdao 266199, China

Ting-ting Li received her bachelor’s degree in atmospheric science and master’s degree in physical oceanography from Ocean University of China in 2016 and 2018 respectively. She is currently teaching at the Naval Submarine Academy. Her research field is ocean remote sensing and simulation.

Li-ming Yuan, Navy Submarine Academy, Qingdao 266199, China; CSSC Ocean Exploration Technology Institute Co., Ltd, Wuxi 214028, China

Li-ming Yuan received her Bachelor’s degree in Surveying Engineering from Shandong University of Science and Technology in 2016, Master degree in Photogrammetry and Remote Sensing from Ocean University of China in 2019. She works as a research and development engineer in CSSC Ocean Exploration Technology Institute Co., Ltd., with a title of assistant engineer. Her research interests are ocean remote sensing and big data analysis, and published 1 sci paper.

Lu Yu, Navy Submarine Academy, Qingdao 266199, China

Lu Yu received his B.Sc. and M.Sc degrees in Radar Engineering from Naval University of Engineering, China, and Ph.D. degree in Control Science and Engineering from Naval Aviation University, China. He is now working at Naval Submarine Academy as a researcher. His main research area including information analysis of remote sensing data, target detection and machine learning.

Jie Chen, Navy Submarine Academy, Qingdao 266199, China

Jie Chen is a scientific research staff member of the Navay Submarine Academy. She graduated in 2010 and obtained a doctor’s degree. Her major is computer application. She has been engaged in marine remote sensing technology research for many years.

Biao Chen, Navy Submarine Academy, Qingdao 266199, China

Biao Chen, professor and doctoral supervisor. In July 1982, he graduated from Naval University of Engineering with a bachelor’s degree in physics. In July 1991, he graduated from China Ocean University with a master’s degree in marine physics. Since 2011, he has been an expert of the 701 subject expert group of the National 863 program and a specially invited expert of the national satellite application expert group. In 2011, he has enjoyed the special allowance of the State Council. Professor Chen Biao has been engaged in the research of marine environment satellite application technology and remote sensing detection technology for a long time, and has obtained outstanding achievements.

Bao-qiang Zhang, Navy Submarine Academy, Qingdao 266199, China; CSSC Ocean Exploration Technology Institute Co., Ltd, Wuxi 214028, China

Bao-qiang Zhang, who has a bachelor’s degree and a master’s degree in geological engineering from Ocean University of China. After graduation, he first worked in the national marine technology center, and then worked as a R & amp; D Engineer in the Institute of marine exploration technology of China Shipbuilding Corporation. At present, his research field mainly focuses on the observation and feature extraction of small and medium scale ocean phenomena.

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Published

2021-03-16

How to Cite

Xu, S.- qin ., Jiang, H., Li, T.- ting ., Yuan, L.- ming ., Yu, L. ., Chen, J. ., Chen, B. ., & Zhang, B.- qiang . (2021). A High Autonomous Sea Front Detection Algorithm Based on SAR Data. Journal of Web Engineering, 20(2), 471–490. https://doi.org/10.13052/jwe1540-9589.20211

Issue

2021: Vol 20 Iss 2

Section

Advanced Practice in Web Engineering