AFOD Regularization for Super-Resolution Reconstruction

In this paper, we present a new regularization-based approach to construct a high-resolution image. The objective functional of the approach consists of a data fidelity term and a regularization term based on anisotropic fourth-order diffusion (AFOD) prior. To evaluate and prove the performance of the proposed method, series of experiments and comparisons with some existing methods including bi-cubic interpolation method and bilateral total variation method are carried out in the paper. Numerical results based on qualitative and quantitative evaluation can indicate that our algorithm is effective.