A UAV detection framework based on dual stereo vision system for low-altitude urban background

This paper establishes a dual stereo vision system and uses Zhang's calibration method to calculate the homography matrix and various parameters of the binocular camera to achieve system correction. The effect of different processing methods on the UAV image in a low-altitude urban background is analyzed. A multistage filter fusion algorithm combined with various filtering and segmentation methods is designed to realize the background suppression of the low-altitude urban background UAV image and drone target extraction. An improved image processing method is used to suppress the background of a single frame image of a video sequence. The image information other than the UAV is regarded as noise or background. The noise and background are subtracted to finally get the UAV image. This research provides a framework for UAV detection in low-altitude airspace, which can support urban airspace management.