A Robust Alternating Direction Method for Constrained Hybrid Variational Deblurring Model

In this work, a new constrained hybrid variational model is presented for spatially-invariant image deblurring. This model combines the non-convex first- and second-order total variation regularizers, which can keep a good balance between preserving image details and alleviating ringing artifacts. To guarantee the deblurring accuracy and robustness, an iteratively reweighted algorithm based on alternating direction method of multipliers is introduced to effectively solve the constrained hybrid variational deblurring model. The experimental results demonstrate the superior performance of the proposed method in terms of objective and subjective image quality assessments.