Cosmic rays interfere with target recognition and extraction and this is a common phenomenon detected in charge-coupled device （CCD） and complimentary metal-oxide semiconductor images taken in space. In this study， we proposed a recognition algorithm based on stellar astrometry for space astronomical images， enabling us to extract a total of 29 731 cosmic-ray events in the 230 CCD images taken by the Chang'e-3 Lunar-based Ultraviolet telescope （LUT）. On the one hand， this number was 11.14% more than the one detected by traditional Laplace algorithm， which was primarily because of events detected with a shape similar to a star. On the other hand， our algorithm failed for only 1.93% of the cases detected by the Laplace algorithm. Among these failed cases， 48.64% were stars， indicating misidentification by the Laplace algorithm. In addition， although peaks appeared at a higher value， the distribution of the electron deposition on the LUT CCD was comparable with those reported for the two Hubble Space Telescope CCDs. With a two-dimensional distribution of the incident angle of cosmic rays on the CCD surface， we identified significant excesses in two directions， which could be understood by a smaller equivalent aluminum thickness of the Chang 'e-3 lander. Finally， we built a public library of cosmic rays recorded by the LUT CCD by extracting the patterns of all the detected cosmic rays， which might be useful for future space telescope image simulation systems.