Automatic boat detection based on diffusion and radiation characterization of boat lights during night for VIIRS DNB...

Visible infrared imaging radiometer suite (VIIRS) day/night band (DNB) data has been used to detect lit boats during night as it is very sensitive to low radiances. The existing methods for boat detection from VIIRS DNB data are mainly based on thresholds that are estimated by the statistical characteristics of pixels or artificial experience. This may generate detection errors and poor adaptability due to the lack of characterization of boat lights. In this paper, a two-step threshold detection algorithm based on the point spread and the radiative characteristics of nightlight point sources is proposed, so that the interference from adjacent pixels could be reduced as much as possible and a reasonable threshold could be determined. Meanwhile, this algorithm is applied to three study areas, namely the sea area around Tianjin Port in Bohai Sea, the sea area around Shanghai Port in East China Sea, and the sea area around Port Sulphur in Gulf of Mexico. It is demonstrated that the detection precision of the proposed algorithm reaches up to 90% and the recall rate reaches up to 85% in three areas when validated by visual interpretation, and the precision is 85.71% when validated by automatic identification system (AIS) data in the study area of the sea area around Port Sulphur in Gulf of Mexico, which approximately increases by 5% compared with the previous algorithm.