A novel iterative image restoration algorithm using nonstationary image priors
In this paper, we propose a novel algorithm for image restoration based on combining nonstationary edge-preserving priors. We develop a Bayesian modeling followed by an evidence analysis inference approach for deriving the foundations of the proposed iterative restoration algorithm. Simulation results over a variety of blurred and noisy standard test images indicate that the presented method outperforms current state-of-the-art image restoration algorithms. We finally present experimental results by digitally refocusing images captured with controlled defocus, successfully confirming the ability of the proposed restoration algorithm in recovering extra features and details, while still preserving edges.