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.
This work is supported in part by “the National Natural Science Foundation of China under Grant, 61331021”.
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Liu, G., Chen, E., Qi, L., Tie, Y., Liu, D. (2016). A Sea-Land Segmentation Algorithm Based on Sea Surface Analysis. In: Chen, E., Gong, Y., Tie, Y. (eds) Advances in Multimedia Information Processing - PCM 2016. PCM 2016. Lecture Notes in Computer Science(), vol 9916. Springer, Cham. https://doi.org/10.1007/978-3-319-48890-5_47
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DOI: https://doi.org/10.1007/978-3-319-48890-5_47
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