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Fast Algorithms for the Anisotropic LLT Model in Image Denoising

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(k2). 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.

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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.

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