A real-time target detection algorithm for Infrared Search and track system based on ROI extraction

With regard to the difficulties confronted in the target detection of circumferential scan infrared search system, such as large image data quantity, low detection probability of weak target, high false detection rate, et al. a real-time target detection algorithm is proposed based on region of interest (ROI) extraction. Firstly, it extracts the ROI of the suspected targets by quick real-time algorithm in the whole panorama image, based on the high frequency and movement characteristics of the target pixels. And then, focusing on the suspected target sliced images of ROI, it has further delicate detection and recognition to exclude those false jamming. The detection result of the test images shows, the algorithm has realized stable detection with low-rate false alarm for distant dim targets, and has been applied to the engineering sample of the Panorama Infrared Search and Tracking system.