Fast Algorithms for the Anisotropic LLT Model in Image Denoising
Year: 2011
East Asian Journal on Applied Mathematics, Vol. 1 (2011), Iss. 3 : pp. 264–283
Abstract
In this paper, we propose a new projection method for solving a general minimization problems with two L1-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.
You do not have full access to this article.
Already a Subscriber? Sign in as an individual or via your institution
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/10.4208/eajam.231210.260411a
East Asian Journal on Applied Mathematics, Vol. 1 (2011), Iss. 3 : pp. 264–283
Published online: 2011-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 20
Keywords: Image denoising anisotropic LLT model Douglas-Rachford splitting method split Bregman method projection method fast projection method.
-
Nonlinear multigrid method for solving the anisotropic image denoising models
Zhang, Jun
Yang, Yu-Fei
Numerical Algorithms, Vol. 63 (2013), Iss. 2 P.291
https://doi.org/10.1007/s11075-012-9623-5 [Citations: 3]