A-contrario detection of hot sources in night-time viirs images

We propose a statistically based method to detect hot sources in night-time data from the Visible Infrared Imaging Radiometer Suite (VIIRS). This instrument is aboard three satellites and collects nearly global night-time imagery every day. Our method looks for bright pixels in at least two spectrally adjacent bands, and for groups of bright pixels close on the ground. Four near- to short-wave infrared bands are used, as well as a middle-wave infrared band after background subtraction. Thresholds are set automatically using the a-contrario framework. The algorithm has thus only one parameter with a clear signification: the expected number of false detections that can be tolerated in one image. A comparison to detections reported in VIIRS Nightfire shows that the proposed technique enables the detection of some supplementary points with weak signals.