A novel variable exponent non-convex TVp,q(x) model in image restoration

Most of the existing image restoration methods either fail to preserve edges or produce a staircase effect and over-smooth phenomenon. To overcome these drawbacks, this paper proposes a novel variable exponent non-convex TVp,q(x) model in image restoration. The proposed method combines a TVp regularization and a TVq(x) regularization and inherits the advantages of TVp model and TVq(x) model well. The proposed model avoids the staircase effect while preserving good edges. The iterative support shrinking algorithm with proximal linearization (ISSAPL) is employed to solve the proposed variable exponent model. Experimental results illustrate the effectiveness of the proposed model in image restoration.