Bo Li
ABSTRACT
Shipborne radar is an indispensable target detection instrument during navigation. Based on the shipborne radar image collected by the Yukun teaching-training ship of Dalian Maritime University, a highlight targets extraction method is proposed here. First, the original shipborne radar image is transformed from polar coordinate system into Cartesian coordinate system. Second, the improved Sobel operator is used to convolute the shipborne radar image in Cartesian coordinate system. Third, Otsu threshold is used to segment the convoluted image and extract the co-frequency interference noises. Fourth, the distance weighted linear filter is used to suppress the co-frequency interference noises. Fifth, the gray correction matrix is used to adjust the overall gray level of the image. Then, the threshold method is used to get the rough highlight targets segmentation. After that, the speckle noises are suppressed by the pixel number threshold. Finally, the result image is transformed back to the polar coordinate system. Experimental results show that our method can effectively segment the highlighted targets in the original shipborne radar image.
- Ying Lu, Shijun Ying, Zhen Sun, Chaojian Shi, Xuping Zou. 2012. Target detection algorithm for marine radar based on maximum likelihood estimate. Journal of Shanghai Maritime University, 33, 4, 1-4. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=SHHY201204000&DbName=CJFQ2012.Google Scholar
- Chihiro Nishizaki, Yasuyuki Niwa, Motonobu Imasato, and Hisaya Motogi. 2014. A method for feature extraction and classification of marine radar images. In Proceedings of 2014 World Automation Congress (WAC). IEEE, Waikoloa, HI, 48-53. https://doi.org/10.1109/WAC.2014.6935652.Google ScholarCross Ref
- Chenxi Hu. 2018. Target recognition for marine radar using Deep Learning methods. Informatization Research, 44, 2, 63-67. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=DZGS201802013&DbName=CJFQ2018Google Scholar
- Deni Yulian, Risanuri Hidayat, Hanung Adi Nugroho, A. Andaya Lestari, and F. Prasaja. 2017. Automated ship detection with image enhancement and feature extraction in FMCW marine radars. In Proceedings of 2017 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications (ICRAMET), IEEE, Jakarta, Indonesia, 58-63. https://doi.org/10.1109/ICRAMET.2017.8253145.Google Scholar
- Haixia Wang, Jin Xu, Qingming Wang, Yang Zhao, and Xibin Pang. 2020. Research on data fusion method of marine radar and electronic chart. Radio Communications Technology, 6, 1, 126-132. https://doi.org/ 10.3969/j.issn.1003-3114.2020.01.018.Google Scholar
- Jin Xu, Baozhu Jia, Xinxiang Pan, Ronghui Li, Liang Cao, Can Cui, Haixia Wang, Bo Li. 2020. Hydrographic data inspection and disaster monitoring using shipborne radar small range images with electronic navigation chart. PeerJ Computer Science, 6, e290. https://doi.org/10.7717/peerj-cs.290.Google ScholarCross Ref
- Nobuyuki Otsu. 2007. Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems Man & Cybernetics, 9, 1, 62-66. https://doi.org/10.1109/TSMC.1979.4310076.Google ScholarCross Ref
Index Terms
- Highlight Target Extraction Method based on X-band Shipborne Radar Image
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