Inshore Ship Detection In High Resolution Satellite Images: Approximation Of Harbours Using Sea-Land Segmentation

This paper proposes a novel inshore ship detection method that is based on the approximation of harbour area with piecewise linear line segments. The method heavily depends on a very fine sea-land segmentation, which is realized in two steps in this work. First, an initial mask is generated by thresholding the normalized difference water index (NDWI) using the zero-level of available global elevation data. In the second step, border of the segmentation result is further enhanced via graph-cut algorithm since spectral characteristics of sea close to sea-land border may differ from the ones of deep parts of the sea. The resultant borderline is used for finding line segments that are assumed to represent the man-made harbours. After being merged and eliminated properly, these line segments are used to extract harbour area so that the remaining connected components of the binary mask can be tested for being ship according to their shapes. Test results show that the proposed method is capable of detecting different kinds of ships in a variety of sea states.