Image Denoising with an Adaptively Weighted Four-Directional Total Variation Method

In this paper, an adaptively weighted four-directional total variation method (Ada-4WTV) is introduced to restore the image corrupted by additive Gaussian noise. In the Ada-4WTV, the trade-off parameter between regularization term and the data fidelity term is adaptive, which can help to deal with textures and smooth areas separately. What´s more, four weights are designed in the TV regularization to preserve the textures and edges better. The boundary conditions are then also considered in the Ada-4WTV. Furthermore, the fast gradient projection (FGP) is extended to implement the Ada-4WTV. The experimental results indicate that the Ada-4WTV adapts to different noise levels and has better performance on keeping the image textures and edges.