Abstract
Waterline extraction is of importance for safe navigation and environment protection. However, the existing pixel-based method failed to get accurate edges due to the similar features between land and interference. This paper proposes a minimum ratio with the mean and standard variation as similarity measure, and presents an improved region merging criterion which based on superpixels for waterline extraction. Utilizing the Envisat and Radarsat images, experiments show the proposed method can effectively extract the waterline and demonstrate better performance in contrast with some existing pixel-based algorithms.
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References
Modava M, Akbarizadeh G (2017) Coastline extraction from SAR images using spatial fuzzy clustering and the active contour method. Int J Remote Sens 38(2):355–370
Fan J, Chu J, Jiang D et al (2015) Remote sensing images coastline detection based on geometric active contour models. In: IEEE sixth international conference on intelligent control and information processing. Wuhan, China, pp 362–366
Liu Z, Li F, Li N, Wang R, Zhang H (2016) A novel region-merging approach for coastline extraction from sentinel-1A IW mode SAR imagery. IEEE Geosci Remote Sens Lett 13(3):324–328
Liu C, Xiao Y, Yang J (2017) A coastline detection method in polarimetric SAR images mixing the region-based and edge-based active contour models. IEEE Trans Geosci Remote Sens 55(99):1–13
Achanta R, Shaji A, Smith K et al (2012) SLIC superpixels compared to state-of-the-art superpixel methods. IEEE Trans Pattern Anal Mach Intell 34(11):2274–2282
Sander J, Ester M, Kriegel HP et al (1998) Density-based clustering in spatial databases: the algorithm GDBSCAN and its applications. Data Min Knowl Disc 2(2):169–194
Wei QR, Feng DZ, Xie H (2016) Edge detector of SAR images using crater-shaped window with edge compensation strategy. IEEE Geosci Remote Sens Lett 13(1):38–42
Ayed IB, Mitiche Z, Belhadj Z (2005) Multiregion level-set partitioning of synthetic aperture radar images. IEEE Trans Pattern Anal Mach Intell 27(5):793–800
Wang L, He L, Mishra A et al (2009) Active contours driven by local Gaussian distribution fitting energy. Sig Process 89(12):2435–2447
Wang F, Wu Y, Fan J et al (2014) Synthetic aperture radar image segmentation using fuzzy label field-based triplet markov fields model. IET Image Proc 8(12):856–865
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Liu, X., Shi, X., Wang, Z., Li, L. (2020). Waterline Extraction Based on Superpixels and Region Merging for SAR Images. In: Liang, Q., Wang, W., Liu, X., Na, Z., Jia, M., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2019. Lecture Notes in Electrical Engineering, vol 571. Springer, Singapore. https://doi.org/10.1007/978-981-13-9409-6_300
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DOI: https://doi.org/10.1007/978-981-13-9409-6_300
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