AI 中文总结
研究KMTNet图像中CCD拖影问题，提出像素级掩膜算法，利用拖影阈值、指数及终止标准确定拖影范围，通过生成候选掩膜优化参数，经插值清理提高源完整性和测光精度，为减轻拖影伪像提供实用框架。
AI 中文摘要
天文电荷耦合器件（CCD）图像常受亮源拖影影响，产生沿列排列的条纹，降低源检测和测光效果。我们提出一种用于韩国微引力透镜望远镜网络（KMTNet）图像拖影的像素级掩膜算法，其中这些条纹沿探测器列远离读出寄存器延伸。该算法使用保守的拖影阈值和量化沿预期拖影方向的过量信号的拖影指数来识别产生拖影的像素。然后根据基于背景相对检测阈值和连续性条件的终止标准确定每个拖影轨迹的范围。为优化这些终止参数，我们生成多个候选掩膜并用类似F-beta分数评估，该分数在保持受拖影影响测光的源的恢复的同时有利于高纯度。使用最终掩膜，我们应用基于插值的清理，并以盖亚DR3为参考评估在拥挤的KMTNet场中的完整性和测光精度方面的性能。源完整性从94.08%提高到98.61%，主要是通过实现先前因拖影而受阻的正确孔径放置。对于选定的受拖影影响的源，均方根测光偏移从0.623星等降至0.068星等。这些结果表明该算法为减轻KMTNet图像中的拖影伪像提供了实用框架。我们还进一步研究了该算法在不同观测条件下的稳定性并讨论了当前掩膜和清理程序的局限性。
英文摘要
Astronomical CCD images are often affected by bleeding from bright sources, producing column-aligned streaks that degrade source detection and photometry. We present a pixel-level masking algorithm for bleeding in Korea Microlensing Telescope Network (KMTNet) images, in which these streaks extend along detector columns away from the readout register. The algorithm identifies bleed-generating pixels using a conservative bleeding threshold and a bleeding index that quantifies excess signal along the expected bleeding direction. The extent of each bleed trail is then determined by termination criteria based on a background-relative detection threshold and a continuity condition. To optimize these termination parameters, we generate multiple candidate masks and evaluate them with an F-beta-like score that favors high purity while preserving recovery of sources whose photometry is biased by bleeding. Using the final mask, we apply interpolation-based cleaning and assess the performance in terms of completeness and photometric accuracy in a crowded KMTNet field, using Gaia DR3 as a reference. The source completeness improves from 94.08% to 98.61%, primarily by enabling proper aperture placement that was previously hindered by bleeding. For selected bleeding-affected sources, the root-mean-square photometric offset decreases from 0.623 mag to 0.068 mag. These results demonstrate that the algorithm provides a practical framework for mitigating bleeding artifacts in KMTNet images. We further examine the stability of the algorithm across different observing conditions and discuss limitations of the current masking and cleaning procedure.
Comments13 pages, 12 figures. Accepted for publication in the Journal of the Korean Astronomical Society (JKAS)
