Detecting geo debris images via voting of motion trajectory features

In this work, we propose a novel technique to detect and track images of debris 011 Geosynchronous Earth Orbit (GEO). As for ground-based observations using high-resolution CCD camera, some effective techniques have been proposed to detect and track the debris images for the GEO region in the past studies. Most of them treat stepwise methods starting at image preprocessing, such as binarization, noise removal, etc. However, image preprocessing algorithms sometimes need to adjust the parameters included in them in arbitrary manner, and they may cause enormous computational time or removal of faint and small debris images. In this study, aiming at more directly estimating debris trajectories from the original time-series imagery, a detecting and tracking method for the debris images based on a voting algorithm is proposed. Focusing on a search observation approach, most of the stars and the debris on GEO appear to be point-like in the image frames, and the trajectories of them are approximated to be line segments in the spatiotemporal domain for relatively short time slot. While the star images are more populous and brighter than the debris images in the image frames, their motion trajectories are more distinguishing than the trajectories of debris images. Therefore, considering such characteristic motions of the celestial objects in the image sequence, the star images are effectively removed by a histogram voting. Consequently, the exact debris images can be detected as the trajectories which linearly move in constant velocities in the group of the remaining debris candidate objects. The effectiveness of the proposed method is validated through a test measurement using real image sequences.