Abstract
Satellite-based synthetic aperture radar (SAR) is a powerful tool for ship detection because it can work in all weather conditions, day and night. However, speckles and heterogeneous regions in SAR images pose great challenges on automatic detection of ships. This paper introduces a bottom-up visual attention model and proposes a visual attention based method for ship detection in SAR images. The proposed method is very simple and fast in computation, and has powerful capability of targets detection. The analysis of the detection performance over both simulated and real images confirms the robustness of the proposed algorithm.
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Yu, Y., Ding, Z., Wang, B., Zhang, L. (2010). Visual Attention-Based Ship Detection in SAR Images. In: Zeng, Z., Wang, J. (eds) Advances in Neural Network Research and Applications. Lecture Notes in Electrical Engineering, vol 67. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12990-2_32
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DOI: https://doi.org/10.1007/978-3-642-12990-2_32
Publisher Name: Springer, Berlin, Heidelberg
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