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For detecting infrared time-sensitive weak and small targets in a complex air-ground background, it is easy to be interfered by low signal-to-noise ratio and strong noise. In this paper we proposed an infrared time-sensitive weak and small target detection method based on density search and gradient decision. First, we use adaptive wiener filtering to preprocess the infrared image to reduce noise interference; then, use the density peak search method to extract points of interest, and use the eight-directional gradient method to make decision-making judgments; finally, use the adaptive threshold segmentation method to extract true targets. The experimental results show that this method has good robustness and detection performance for single infrared time-sensitive weak and small target detection in the air-ground background.

Infrared time-sensitive weak and small target detection method based on density search and gradient decision