Diagonal total variation regularization criterion for fast convergence
Satoshi Kiriyama, Tomoyuki Usui, Tomio Goto, Satoshi Hirano, Masaru Sakurai, Takahiro Saito · 2010
The total variation (TV) regularization method is very attractive for various image processing applications. In order to apply the TV approach to motion pictures, it is required to reduce the computational time of the iterative signal processing of the TV regularization. In this paper, we propose the diagonal TV criterion instead of conventional isotropic or anisotropic TV criteria. The experimental results show that we can obtain almost half of the iteration number both in the steepest descent algorithm and Chambolle's algorithm by utilizing the diagonal TV compared with the conventional TV criteria.