TY - JOUR
T1 - Fast Algorithms for the Anisotropic LLT Model in Image Denoising
JO - East Asian Journal on Applied Mathematics
VL - 3
SP - 264
EP - 283
PY - 2018
DA - 2018/02
SN - 1
DO - http://doi.org/10.4208/eajam.231210.260411a
UR - https://global-sci.org/intro/article_detail/eajam/10908.html
KW - Image denoising, anisotropic LLT model, Douglas-Rachford splitting method, split Bregman method, projection method, fast projection method.
AB - <p style="text-align: justify;">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.</p>