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A Novel Ship Detection Method Based on Sea State Analysis from Optical Imagery

This paper proposes a novel ship detection method based on analyzing the sea state in optical images. This method is composed of three phases. First, the image is segmented with the improved region splitting and merging method, which divides the sea into separated regions. Then, the sea state of each divided region of sea is analyzed by extracting texture roughness and ripple density of a modified differential box counting (DBC) method. Finally, an appropriate algorithm is applied to detect ships for each region of sea. Experimental results test on 36 real remote sensing images and 133 images obtained from Google earth demonstrate that the method is free of image resolution and has little limitation of sea conditions.