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Photometric surveys have provided incredible amounts of astronomicalinformation in the form of images. However, astronomical images often containartifacts that can critically hinder scientific analysis by misrepresentingintensities or contaminating catalogs as artificial objects. These affectedpixels need to be masked and dealt with in any data reduction pipeline. In thispaper, we present a flexible, iterative algorithm to recover (unmask)astronomical images where some pixels are lacking. We demonstrate theapplication of the method on some intensity calibration source images in COMulti-line Imaging of Nearby Galaxies (COMING) Project conducted using the 45mtelescope at Nobeyama Radio Observatory (NRO). The proposed algorithm restoredartifacts due to a detector error in the intensity calibration source images.The restored images were used to calibrate 11 out of 147 observed galaxy mapsin the survey. The tests show that the algorithm can restore measuredintensities at sub 1% error even for noisy images (SNR = 2.4), despite lackinga significant part of the image. We present the formulation of thereconstruction algorithm, discuss its possibilities and limitations forextensions to other astronomical signals and the results of the COMINGapplication.

A Method for Unmasking Incomplete Astronomical Signals: Application to CO Multi-line Imaging of Nearby Galaxies Project