Iterative PCA approach for blind restoration of single blurred image
This paper proposes a single-channel image blind restoration using iterative principal components analysis (PCA) to improve the quality of restoration. Previously proposed PCA approaches for blind restoration have a lot of problems. For example, the process of boosting high-frequency components would be improvable, no numerical evaluation has been performed, and etc. Generating an ensemble by means of Gaussian filter application, discussed in this paper, could improve to extract the high frequency components which had been lost. Furthermore, iterative PCA boosts the high frequency components. Our proposed method is applied to a restoration example of atmospheric turbulence-degraded imagery, and we verified to improve restoration quality in comparisons with conventional methods. For demonstrating comparative experiments, simulations have been conducted. From the results, we can confirm that the proposed method gives higher PSNR as well as SSIM than the conventional methods.