@Article{EAJAM-1-3,
author = {},
title = {Fast Algorithms for the Anisotropic LLT Model in Image Denoising},
journal = {East Asian Journal on Applied Mathematics},
year = {2011},
volume = {1},
number = {3},
pages = {264--283},
abstract = {<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>},
issn = {2079-7370},
doi = {https://doi.org/10.4208/eajam.231210.260411a},
url = {https://global-sci.com/article/82872/fast-algorithms-for-the-anisotropic-llt-model-in-image-denoising}
}