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Optical characterization of space objects generally involves the observation of an object of interest as it passes over a ground-based imaging asset. Owing to the presence of turbulence, adaptive optics, post-processing, or a combination thereof, is used to enhance imagery. Specular glints, often present in such imagery, can introduce severe artifacts after post-processing methods are applied. Removing these artifacts generally involves excluding frames that include glints. With fewer frames, image reconstruction quality is reduced and in some cases entire collections are discarded. We describe a method where Robust Alignment by Sparse Low-rank decomposition (RASL) is used to identify and exclude glints from sets of turbulence-corrupted imagery. A number of simulated image sets including glints were generated and the RASL algorithm applied. We show that RASL is capable of identifying glints in these images. Once identified, glints are removed or masked. Post-processing using corrected imagery results in reconstructions free from severe artifacts.