Abstract

Fast and robust detection of infrared small targets in a single image has always been challenging. The background residue in complex ground–sky background images leads to high false alarm rates when traditional local contrast methods are used because of the complexity and variability of the ground–sky background imaging environment. A weighted local ratio-difference contrast (WLRDC) method is proposed in this paper to address this problem and detect infrared small targets in the ground–sky background. First, target candidate pixels are obtained using a simple facet kernel filter. Second, local contrast saliency maps and weighted mappings are calculated on the basis of the local ratio-difference contrast and the spatial dissimilarity of the target, respectively. Third, the final weighted mapping can be obtained through the multiplication fusion strategy. Finally, a simple threshold segmentation method is employed to extract the target. Experimental results on six real ground–sky infrared scenes showed that the proposed method outperforms existing state-of-the-art methods.

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