Fast ship detection from optical satellite images based on ship distribution probability analysis

Automatic ship detection from optical satellite images remains a tough task. In this paper, a novel method of ship detection from optical satellites is proposed by analyzing the ship distribution probability. First, an anomaly detection model is constructed by the sea cluster histogram model; then, the ship distribution based on the ship safety navigational criterion is analyzed to obtain the ship candidates, and obvious non-ship objects are removed by the area properties from ship candidates; finally, a structural continuity descriptor is designed to remove false alarms from the ship candidates. Experiments on numerous satellite images from panchromatic and one band within multispectral sensors are conducted. The results verified that the proposed method outperforms existing methods in both effectiveness and efficiency.