This paper proposes a single-channel image blind restoration by using iterative principal components analysis (PCA). Previously we proposed the iterative PCA approaches for blind restoration and proved its superiority over conventional methods. Still, there are some problems to be solved. One of them is precise and automatic way to determine the iteration number. This study tries to solve this by applying a blind image quality assessment for automatic optimization of the iterative number. For a verification example of atmospheric turbulence-degraded imagery our proposed method provides better improved restoration quality than conventional methods. In addition, experiments of simulations are conducted for real images. From the results, we can confirm that the proposed method gives higher PSNR as well as SSIM than the conventional methods even in real environments.