The magic of split augmented Lagrangians applied to K-frame-based l0–l2 minimization image restoration

We propose a simple, yet efficient image deconvolution approach, which is formulated as a complementary K-frame-based l0–l2 minimization problem, aiming at benefiting from the advantages of each frame. The problem is solved by borrowing the idea of alternating split augmented Lagrangians. The experimental results demonstrate that our approach has achieved competitive performance among state-of-the-art methods.