@Article{EAJAM-1-264, author = {}, title = {Fast Algorithms for the Anisotropic LLT Model in Image Denoising}, journal = {East Asian Journal on Applied Mathematics}, year = {2018}, volume = {1}, number = {3}, pages = {264--283}, abstract = {

In this paper, we propose a new projection method for solving a general minimization problems with two $L^1$-regularization terms for image denoising. It is related to the split Bregman method, but it avoids solving PDEs in the iteration. We employ the fast iterative shrinkage-thresholding algorithm (FISTA) to speed up the proposed method to a convergence rate $O$($k^-$$^2$). We also show the convergence of the algorithms. Finally, we apply the methods to the anisotropic Lysaker, Lundervold and Tai (LLT) model and demonstrate their efficiency.

}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.231210.260411a}, url = {http://global-sci.org/intro/article_detail/eajam/10908.html} }