Photometric surveys have provided incredible amounts of astronomical information in the form of images. However, astronomical images often contain artifacts that can critically hinder scientific analysis by misrepresenting intensities or contaminating catalogs as artificial objects. These affected pixels need to be masked and dealt with in any data reduction pipeline. In this paper, we present a flexible, iterative algorithm to recover (unmask) astronomical images where some pixels are lacking. We demonstrate the application of the method on some intensity calibration source images in CO Multi-line Imaging of Nearby Galaxies (COMING) Project conducted using the 45m telescope at Nobeyama Radio Observatory (NRO). The proposed algorithm restored artifacts due to a detector error in the intensity calibration source images. The restored images were used to calibrate 11 out of 147 observed galaxy maps in the survey. The tests show that the algorithm can restore measured intensities at sub 1% error even for noisy images (SNR = 2.4), despite lacking a significant part of the image. We present the formulation of the reconstruction algorithm, discuss its possibilities and limitations for extensions to other astronomical signals and the results of the COMING application.

中文翻译：

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一种揭露不完整天文信号的方法：在附近星系的 CO 多线成像项目中的应用

光度测量以图像的形式提供了数量惊人的天文信息。然而，天文图像通常包含伪影，这些伪影会通过将强度误传或将目录污染为人造物体而严重阻碍科学分析。这些受影响的像素需要在任何数据缩减管道中进行屏蔽和处理。在本文中，我们提出了一种灵活的迭代算法来恢复（取消屏蔽）缺少某些像素的天文图像。我们演示了该方法在使用 Nobeyama 射电天文台 (NRO) 的 45m 望远镜进行的附近星系 CO 多线成像 (COMING) 项目中的一些强度校准源图像上的应用。由于强度校准源图像中的检测器错误，所提出的算法恢复了伪影。恢复的图像用于校准调查中观察到的 147 张星系图中的 11 张。测试表明，即使对于噪声图像 (SNR = 2.4)，该算法也可以以低于 1% 的误差恢复测量强度，尽管缺少图像的重要部分。我们介绍了重建算法的公式，讨论了其扩展到其他天文信号的可能性和局限性以及 COMING 应用程序的结果。