Abstract
Ship detection from optical remote sensing imagery is an important and challenging task. Sea-land segmentation is a key step for ship detection. Due to the complex and various sea surfaces caused by waves, illumination and shadows, traditional sea-land segmentation algorithms often misjudge between land and sea. Thus, a new segmentation scheme based on sea surface analysis is proposed in this paper. Then the adaptive threshold can be determined according to statistical analysis to different types of patches from the optical remote sensing images. Experimental results show that our algorithm has better performance compared to the traditional algorithms.
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CITATION STYLE
Liu, G., Chen, E., Qi, L., Tie, Y., & Liu, D. (2016). A sea-land segmentation algorithm based on sea surface analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9916 LNCS, pp. 479–486). Springer Verlag. https://doi.org/10.1007/978-3-319-48890-5_47
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