The task of segmenting small infrared targets, which have few pixels and weak features, has been a difficult problem in the field of small target image processing. Small targets exist not only in general images, but also widely in UAV cameras, communication base station cameras, rescue cameras and vehicle cameras. The study of small target segmentation algorithms is very important for analyzing and utilizing these images, and has important applications in security, transportation, and rescue. Traditional small target segmentation algorithms are able to segment objects with simple target contour edges and large differences in signal strength. The traditional algorithm often has high false detection rate and missed detection rate when facing several targets with weak signal strength, and does not perform well in complex scenes. In this paper, we introduce an infrared small target segmentation scheme facing multiple types and numbers of targets. We also produce an infrared UAV and pedestrian dataset for validation.
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