Call For Paper - Upcoming Conferences

Research Article | Open Access
Volume 8 | Issue 5 | Year 2021 | Article Id. IJECE-V8I5P101 | DOI : https://doi.org/10.14445/23488549/IJECE-V8I5P101

Ship Detection in Medium-Resolution SAR Images using Deep learning

M.Muruga Lakshmi, Dr.S.Thayammal

Citation :

M.Muruga Lakshmi, Dr.S.Thayammal, "Ship Detection in Medium-Resolution SAR Images using Deep learning," International Journal of Electronics and Communication Engineering, vol. 8, no. 5, pp. 1-5, 2021. Crossref, https://doi.org/10.14445/23488549/IJECE-V8I5P101

Abstract

Due to its noticeable advantages of working, Synthetic aperture radar (SAR) has become a significant device for many remote sensing applications. The Existing methods for SAR images perform well under some constraints. In this work, a ship detection method based on CNN (Convolutional Neural Network) called VGG net (Visual Geometry Group) is proposed. To improve the performance of ship detection by adopting multi-level features produced by the convolution layers, which fits ships with different sizes. The Simulation results of the proposed method are compared with the existing method

Keywords

Synthetic aperture radar, Convolutional Neural Network.

References

[1] Morillas, J. R. A., Garcia, I. C., &Zolzer, U. (2015).A Hierarchical Ship Detection Scheme for High-Resolution SAR Images.2015 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP). doi:10.1109/iccp.2015.7312682
[2] Martin-de-Nicolas, J., Mata-Moya, D., Jarabo-Amores, M. P., del-Rey-Maestre, N., &Barcena-Humanes, J. L. (2013). Operational Approach For Ship Detection And Classification2013 ‘18th International Conference on Digital Signal Processing (DSP). doi:10.1109/icdsp.2013.6622836 [3] H. Tanveer, T. Balz and B. Mohamdi, Ship target detection and identification based on SSD_MobilenetV2, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), Xiamen, China, (2019)1-5, doi: 10.1109/APSAR46974.2019.9048499.
[4] D. Velotto, M. Soccorsi, and S. Lehner, A new scattering similarity-based metric for ship detection in Pol-SAR image, 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, (2012)7621-7624, doi: 10.1109/IGARSS.2012.6351863.
[5] Y. Liu, H. Ma, Y. Yang, and Y. Liu, "High-Speed Ship Detection in SAR Images by Improved Yolov3, Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, Fuzhou, (2011) 386-388, doi: 10.1109/ICSDM.2011.5969070.
[6] P. Jarabo-Amore, Demonstrator of maritime SAR applications: Automaticship detection results, 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, (2012)3732-3735, doi: 10.1109/IGARSS.2012.6350506.
[7] H. Tanveer, T. Balz, and B. Mohamdi, Using convolutional neural network (CNN) approach for ship detection in Sentinel-1 SAR imagery, 2019 6th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), Xiamen, China, (2019)1-5, doi: 10.1109/APSAR46974.2019.9048499.
[8] D. Velotto, M. Soccorsi, and S. Lehner, Azimuth ambiguities removal for ship detection using full polarimetric X-band SAR Data, 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, (2012)7621-7624, doi: 10.1109/IGARSS.2012.6351863.
[9] W. Ao and F. Xu, Robust Ship Detection in SAR Images from Complex Background, 2018 IEEE International Conference on Computational Electromagnetics (ICCEM), Chengdu, (2018)1-2, doi: 10.1109/COMPEM.2018.8496647.
[10] Y. Liu, H. Ma, Y. Yang, and Y. Liu, Automatic ship detection from SAR images," Proceedings 2011 IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, Fuzhou, (2011)386-388, doi: 10.1109/ICSDM.2011.5969070.
[11] C. Avolio et al., A method for the reduction of ship-detection false alarms due to SAR azimuth ambiguity, 2014 IEEE Geoscience and Remote Sensing Symposium, Quebec City, QC, (2014)3694-3697, doi: 10.1109/IGARSS.2014.6947285.
[12] J. Nan, C. Wang, B. Zhang, F. Wu, H. Zhang, and Y. Tang, Ship wake CFAR detection algorithm in SAR images based on length normalized scan, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS, Melbourne, VIC, (2013)3562-3565, doi: 10.1109/IGARSS.2013.6723599.
[13] T. ZHANG, X. ZHANG, J. SHI, and S. WEI, High-Speed Ship Detection in SAR Images by Improved Yolov3, 2019 16th International Computer Conference on Wavelet Active Media
Technology and Information Processing, Chengdu, China, (2019)149-152, doi: 10.1109/ICCWAMTIP47768.2019.9067695.
[14] L. Zhai, Y. Li, and Y. Su, Segmentation-based ship detection in the harbor for SAR images, 2016 CIE International Conference on Radar (RADAR), Guangzhou, (2016) 1-4, doi: 10.1109/RADAR.2016.8059479.
[15] Y. Tao, H. Lang, and H. Shi, A new scattering similarity-based metric for ship detection in Pol-SAR image, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, (2018) 9331-9334, doi: 10.1109/IGARSS.2018.8651433.
[16] Y. Gui, X. Li, L. Xue, and J. Lv, A scale transfer convolution network for small ship detection in SAR images, 2019 IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC), Chongqing, China, (2019) 1845-1849, doi: 10.1109/ITAIC.2019.8785805.
[17] R. Wang et al., An Improved Faster R-CNN Based on MSER Decision Criterion for SAR Image Ship Detection in Harbor, IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, (2019) 1322-1325, doi: 10.1109/IGARSS.2019.8898078.
[18] W. Li, B. Zou, and L. Zhang, Ship detection in a large scene SAR image using image uniformity description factor, 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA), Beijing, (2017) 1-5, doi: 10.1109/BIGSARDATA.2017.8124933.
[19] Y. Zou, L. Zhao, S. Qin, M. Pan, and Z. Li, Ship target detection and identification based on SSD_MobilenetV2, 2020 IEEE 5th Information Technology and Mechatronics Engineering Conference (ITOEC), Chongqing, China, (2020) 1676-1680, doi: 10.1109/ITOEC49072.2020.9141734.
[20] T. Kim, S. Oh, T. B. Chun, and M. Lee, Impact of Atmospheric Correction on the Ship Detection Using Airborne Hyperspectral Image," IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, Yokohama, Japan, (2019) 2190-2192, doi: 10.1109/IGARSS.2019.8898766.