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Ship detection using VIIRS sensor specific data

The maritime domain can be a very resource intensive region to actively monitor on a continuous basis. Remote sensing has been observed to be a valuable tool in this application, and the most effective strategy has been to supplement outputs from different Earth Observation tools in order to better classify target objects. The Visible Infrared Imaging Radiometer Suit is able to generate daily images of the earths surface spanning 2000 km; covering the large area of a country's Economic Exclusive Zone. The low level light sensitivity of the Day-Night band enable light sources above the oceans surface to be detected at night, appearing as a bright pixel against the darker ocean background. In this paper we investigate the application of an adaptive threshold method commonly used as a prescreening stage for ship detection in Synthetic Aperture Radar imagery, and compare it to a recently developed method specific to DNB imagery. Our initial application suggests the adaptive threshold method may be able to classify these unusually bright pixels at a slightly better false alarm rate when moon lit conditions are not as favourable and clouds cause an increase in false detections. It has been observed in previous experiments that one algorithm, or even a combination may not be enough to create a robust detection system and additional investigation is needed to develop proceeding stages to identify these false alarms and remove them.