Abstract:

The total variation model can remove noise effectively, however, it also brings in staircase effect. To overcome this shortcoming, we use the second order total generalized variation (TGV) as the regularization term in the new denoising model. The TGV model can not only eliminate the staircase effect, but also preserve structures such as edges and textures better. The nonlocal differential operators which are constructed based on the idea of the nonlocal means filtering algorithm are applied to the TGV model, and the new method makes good use of the global information of the image to remove noise. Experimental results demonstrate the validity and superiority of the proposed method.

Key words: total variational model, total generalized variation, nonlocal means filtering, nonlocal differential operators；image denoising