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An Improved Method of Land Masking for Synthetic Aperture Radar-based Ship Detection

Published online by Cambridge University Press:  26 March 2018

Chan-Su Yang Open the ORCID record for Chan-Su Yang [Opens in a new window] ,
Ju-Han Park  and
Ahmed Harun-Al Rashid
Chan-Su Yang*
Affiliation:
(Marine Safety Research Center, Korea Institute of Ocean Science & Technology, Busan, South Korea) (Integrated Ocean Sciences, University of Science & Technology, Daejeon, South Korea) (Korea Maritime and Ocean University, Busan, South Korea)
Ju-Han Park
Affiliation:
(Marine Safety Research Center, Korea Institute of Ocean Science & Technology, Busan, South Korea)
Ahmed Harun-Al Rashid
Affiliation:
(Marine Safety Research Center, Korea Institute of Ocean Science & Technology, Busan, South Korea) (Integrated Ocean Sciences, University of Science & Technology, Daejeon, South Korea)
*
(E-mail: yangcs@kiost.ac.kr)
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Abstract

Land masking of Synthetic Aperture Radar (SAR) images is generally accomplished by applying either archived shoreline databases or image segmentation. However, those methods cannot be solely applied to geographical areas complicated with many small islands and exposed rocks. Therefore, we have proposed a new procedure where Sobel edge extraction is applied to detect the edges of all objects from KOMPSAT-5 X-band SAR images, followed by a merging process with the edges from the land objects based on Electronic Navigational Chart (ENC) coastlines. Using the land mask data, geometrically corrected SAR images were masked before applying a ship detection algorithm. This land masking procedure was applied to several images covering different areas of the Korean Peninsula. The results show that land targets such as newly constructed and natural objects were also masked, and thus did not create false alarms during ship detection. Therefore, this method can be used to assist precise ship detection using SAR images in coastal waters.

Keywords

Land maskingSARKOMPSAT-5ENC

Information

Type
Research Article
Information
The Journal of Navigation , Volume 71 , Issue 4 , July 2018 , pp. 788 - 804
Copyright
Copyright © The Royal Institute of Navigation 2018 

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References

REFERENCES

Al-amri, S. S., Kalyankar, N. V. and Khamitkar, S. D. (2010). Image Segmentation by using Edge Detection. International Journal on Computer Science and Engineering, 2, 804–807.Google Scholar
Biamino, W., Borasi, M., Cavagnero, M., Croce, A., Di Matteo, L., Fontebasso, F., Tataranni, F. and Trivero, P. (2015). A “Dynamic” Land Masking Algorithm for Synthetic Aperture Radar Images. Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International, 4324–4327.Google Scholar
Boland, M. V. and Murphy, R. F. (2001). A Neural Network Classifier Capable of Recognizing the Patterns of all Major Subcellular Structures in Fluorescence Microscope Images of HeLa Cells. Bioinformatics, 17(12), 1213–1223.Google Scholar
Brusch, S., Lehner, S., Fritz, T., Soccorsi, M., Soloviev, A. and van Schie, B. (2011). Ship Surveillance with TerraSAR-X. IEEE Transactions on Geoscience and Remote Sensing, 49(3), 1092–1103.Google Scholar
Canny, J. (1986). A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 8(6), 679–698.CrossRefGoogle ScholarPubMed
Chaturvedi, S. K., Yang, C. S., Ouchi, K. and Shanmugam, P. (2012). Ship Recognition by Integration of SAR and AIS. Journal of Navigation, 65(2), 323–337.Google Scholar
Costa, C., Antonucci, F., Boglione, C., Menesatti, P., Vandeputte, M. and Chatain, B. (2013). Automated Sorting for Size, Sex and Skeletal Anomalies of Cultured Seabass using External Shape Analysis. Aquacultural Engineering, 52, 58–64.Google Scholar
Costa, C., Negretti, P., Vandeputte, M., Pallottino, F., Antonucci, F., Aguzzi, J., Bianconi, G. and Menesatti, P. (2014). Innovative Automated Landmark Detection for Food Processing: The Backwarping Approach. Food and Bioprocess Technology, 7(8), 2291–2298.Google Scholar
Della Rocca, M. R., Fiani, M., Fortunato, A. and Pistillo, P. (2004). Active Contour Model to Detect Linear Features in Satellite Images. International Archives of Photogrametry, Remote Sensing and Spatial Information Sciences, 35(B3), 446–450.Google Scholar
Dellepiane, S., De Laurentiis, R. and Giordano, F. (2004). Coastline Extraction from SAR Images and a Method for the Evaluation of the Coastline Precision. Pattern Recognition Letters, 25, 1461–1470.Google Scholar
Feng, J., Jiao, L. C., Zhang, X., Gong, M. and Sun, T. (2013). Robust Non-local Fuzzy C-means Algorithm with Edge Preservation for SAR Image Segmentation. Signal Processing, 93(2), 487–499.CrossRefGoogle Scholar
Gao, W., Zhang, X., Yang, L. and Liu, H. (2010). An Improved Sobel Edge Detection. In Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on 2010 July 9, 5, 67–71.Google Scholar
Greidanus, H., Clayton, P., Indregard, M., Staples, G., Suzuki, N., Vachoir, P., Wackerman, C., Tennvassas, T., Mallorquí, J., Kourti, N. and Ringrose, R. (2004). Benchmarking Operational SAR Ship Detection. In Proceedings of International Geoscience and Remote Sensing Symposium (IGARSS) 20–24 September 2004, 4215–4218.CrossRefGoogle Scholar
IHO. (2014). Use of the Object Catalogue for ENC, IHO Special Publication No. 57 (IHO S-57 Appendix B.1, Annex A), Edition 4.0.0, June, 2014, International Hydrographic Organization.Google Scholar
Jeong, H. G., Kotov, A. A. and Lee, W. (2013). A New Species of the Genus Pleuroxus Baird (Cladocera: Anomopoda: Chydoridae) from Jeju Island, South Korea. Zootaxa, 3666(1), 31–40.Google Scholar
Jiang, Q., Wang, S., Ziou, D. and Zaart, A. (1999). Automatic Detection for Ship Targets in RADARSAT SAR Images from Coastal Regions. In Vision Interface'99, Trois-Tivieres, Canada, 131–137.Google Scholar
Karvonen, J. (2015). Evaluation of the Operational SAR Based Baltic Sea Ice Concentration Products. Advances in Space Research, 56(1), 119–132.Google Scholar
Kashyap, Y., Vyas, A., Raghuwanshi, R. and Sharma, R. (2015). Edge Detection using Sobel Method with Median Filter. International Journal of Modern Trends in Engineering and Research, 2(5), 372–378.Google Scholar
Keramitsoglou, I., Cartalis, C. and Kiranoudis, C. T. (2006). Automatic Identification of Oil Spills on Satellite Images. Environmental Modelling & Software, 21, 640–652.Google Scholar
Kim, T. H., Yang, C. S., Oh, J. H. and Ouchi, K. (2014). Analysis of the Contribution of Wind Drift Factor to Oil Slick Movement under Strong Tidal Condition: Hebei Spirit Oil Spill Case. PLoS One, 9(1), e87393.Google Scholar
Kodors, S. and Zarembo, I. (2013). Urban Objects Segmentation using Edge Detection. Environment. Technology. Resources. Proceedings of the 9th International Scientific and Practical Conference, 1(I). Rçzeknes Augstskola, Rçzekne, RA Izdevniecîba.Google Scholar
Krebs, G.D. (2017). “KOMPSAT 5 (Arirang 5),” Gunter's Space Page. http://space.skyrocket.de/doc_sdat/kompsat-5.htm. Accessed 22 February 2017.Google Scholar
Lee, S. R. (2010). Overview of KOMPSAT-5 Program, Mission, and System. Geoscience and Remote Sensing Symposium (IGARSS), 2010 IEEE International.CrossRefGoogle Scholar
Liu, H. and Jezek, K. C. (2004). Automated Extraction of Coastline from Satellite Imagery by Integrating Canny Edge Detection and Locally Adaptive Thresholding Methods. International Journal of Remote Sensing, 25(5), 937–958.Google Scholar
Margarit, G., Barba, J. A. and Tabasco, A. (2009). Operative Ship Monitoring System Based on Integrating AIS Polls within Synthetic Aperture Radar (SAR) Imagery. WIT Transactions on the Built Environment, 108, 325–337.Google Scholar
Mashaly, A. S., AbdElkawy, E. F. and Mahmoud, T. A. (2014). Ship Detection in SAR Images using Efficient Land Masking Methods. Society of Photo-optical Instrumentation Engineers (SPIE) Conference Series (Vol. 9093).Google Scholar
Montuori, A., Nunziata, F. and Migliaccio, M. (2010). A Multi-polarization Approach for SAR Ship Detection. Proceedings of the XVIII RiNEm. Benevento.Google Scholar
Naz, S. and Rao, S. N. (2014). Glaucoma Detection in Color Fundus Images using Cup to Disc Ratio. The International Journal of Engineering and Science, 3, 51–58.Google Scholar
Othman, Z., Haron, H. and Kadir, M. R. A. (2009). Comparison of Canny and Sobel Edge Detection in MRI Images. Computer Science, Biomechanics & Tissue Engineering Group, and Information System, 133–136.Google Scholar
Pelizzari, S. A. (2011). Oil Spill Detection using SAR Images. Doctoral dissertation, Instituto Superior Técnico, Universidade Tecnica de Lisboa, Lisbon, Portugal.Google Scholar
Ramadevi, Y., Sridevi, T., Poornima, B. and Kalyani, B. (2010). Segmentation and Object Recognition using Edge Detection Techniques. International Journal of Computer Science & Information Technology, 2, 153–160.CrossRefGoogle Scholar
Romeiser, R., Breit, H., Eineder, M., Runge, H., Flament, P., De Jong, K. and Vogelzang, J. (2005). Current Measurements by SAR Along-track Interferometry from a Space Shuttle. IEEE Transactions on Geoscience and Remote Sensing, 43(10), 2315–2324.Google Scholar
Senthilkumaran, N. and Rajesh, R. (2009). Edge Detection Techniques for Image Segmentation- A Survey of Soft Computing Approaches. International Journal of Recent Trends in Engineering, 1, 250–254.Google Scholar
Shahane, P. R., Choukade, A. S. and Diyewar, A. N. (2015). Online Signature Recognition using MATLAB. International Journal of Innovative Research in Electrical, Electronics, Instrumentation, and Control Engineering, 32, 107–112.Google Scholar
Shu, Y., Li, J., Yousif, H. and Gomes, G. (2010). Dark-spot Detection from SAR Intensity Imagery with Spatial Density Thresholding for Oil-spill Monitoring. Remote Sensing of Environment, 114(9), 2026–2035.CrossRefGoogle Scholar
SI Imaging Services. (2015). KOMPSAT-5 Product Specifications- Standard Products Specifications. Version 1.2. Korea Aerospace Research Institute. http://www.si-imaging.com/wp-content/uploads/2016/12/KOMPSAT-5_Standard_Products_Specifications_v1.2.pdf. Accessed 27 February 2017.Google Scholar
Simpson, J. J. (1990). On the Accurate Detection and Enhancement of Oceanic Features Observed in Satellite Data. Remote Sensing of Environment, 33(1), 17–33.CrossRefGoogle Scholar
Singh, E. H. and Kaur, E. T. (2013). Implementation of Various Edge Detection Techniques for Gray Scale Images in VC++. International Journal of Emerging Technologies in Computational and Applied Sciences, 6(4), 280–284.Google Scholar
Slater, J. A., Garvey, G., Johnston, C., Haase, J., Heady, B., Kroenung, G. and Little, J. (2006). The SRTM data finishing process and products. Photogrammetric Engineering & Remote Sensing, 72 (3), 237–247.Google Scholar
Sobel, E. C. (1990). The Locust's use of Motion Parallax to Measure Distance. Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology, 167(5), 579–588.Google Scholar
Trivero, P., Adamo, M., Biamino, W., Borasi, M., Cavagnero, M., De Carolis, G., Di Matteo, L., Fontebasso, F., Nirchio, F. and Tataranni, F. (2016). Automatic Oil Slick Detection from SAR Images: Results and Improvements in the Framework of the PRIMI Pilot Project. Deep Sea Research Part II: Topical Studies in Oceanography, 133, 146–158.Google Scholar
Wall, C. C., Muller-Karger, F. E., Roffer, M. A., Hu, C., Yao, W. and Luther, M. E. (2008). Satellite Remote Sensing of Surface Oceanic Fronts in Coastal Waters off West-central Florida. Remote Sensing of Environment, 112(6), 2963–2976.Google Scholar
Wessel, P. and Smith, W. H. F. (1996). A Global Self-consistent, Hierarchical, High-resolution Shoreline Database. Journal of Geophysical Research, 101, 8741–8743.CrossRefGoogle Scholar
Yang, C. S. and Ouchi, K. (2008). Comparison of Ship Detectability using SAR Polarization Data: ENVISAT ASAR AP Mode. Geoscience and Remote Sensing Symposium, 2008. IGARSS 2008. IEEE International, (Vol. 1). IEEE.Google Scholar
Zhang, J. Y., Yan, C. and Huang, X. X. (2009). Edge Detection of Images Based on Improved Sobel Operator and Genetic Algorithms. In Image Analysis and Signal Processing, 2009. IASP 2009. International Conference on 2009 April 2011, 31–35.Google Scholar