Abstract Space debris detection is important for space asset protection and space situational awareness. The current environment of man-made satellites and space debris objects in Earth orbits increases rapidly, so does the probability of collision between them. In this paper, we propose a space debris detection method based on image alignment and connected region analysis. First, the median filter and an improved top-hat filter are used for pre-process of the original images, which can eliminate thermal noises and improve optical distribution integrity of targets. Second, a feasible and easy-to-implement connected region labeling method is used for centroid extraction of suspected targets. Meanwhile, several saliency features of targets are used for suspected targets confirmation and false alarms elimination. Then, we use stars in high-brightness magnitude as feature points for accurate interframe registration, which can suppress the influence of platform shaking and background movement on dim target trajectory associations. Finally, data association is used for target trajectory extraction. The experiment is performed using one astronomical image sequence, the results show that the proposed method is robust and efficient on complex backgrounds.
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