Both deletion and the noise pollution may exist in low-rank images, that is to say, both data loss and destruction occur in low-rank images.In view of the existing problems,this paper proposes a new model combining matrix recovery with matrix completion based on inexactly augmen ted Lagrange multiplier (IALM).It removes the cover and fills the missing parts using low-r ank matrix completion,and simultaneously it gets rid of the noise to obtain the full image using low-rank matrix recovery.For the three different images with noise,comparing their recovery tim e,signal-to-noise ratios,peak signal-to-noise ratios and error rates with those of the existing low-rank matrix algorithm, it can be seen that the improved low-rank matrix completion with recovery model can get rid of the cover noise images very well.In the repairing of obscured images,change the model and recover the cover images.The low-rank matrix completion based on low-rank matrix recovery can remove the cover and fill the missing parts simultaneously.