Author:
Zhang Zhenwei,Li Xue,Duan Yuping,Yin Ke,Tai Xue-Cheng
Abstract
<p style='text-indent:20px;'>We propose an efficient multi-grid domain decomposition method for solving the total variation (TV) minimization problems. Our multi-grid scheme is developed based on the piecewise constant function spanned subspace correction rather than the piecewise linear one in [<xref ref-type="bibr" rid="b17">17</xref>], which ensures the calculation of the TV term only occurs on the boundaries of the support sets. Besides, the domain decomposition method is implemented on each layer to enable parallel computation. Comprehensive comparison results are presented to demonstrate the improvement in CPU time and image quality of the proposed method on medium and large-scale image denoising and reconstruction problems.</p>
Publisher
American Institute of Mathematical Sciences (AIMS)
Subject
Control and Optimization,Discrete Mathematics and Combinatorics,Modelling and Simulation,Analysis,Control and Optimization,Discrete Mathematics and Combinatorics,Modeling and Simulation,Analysis
Reference41 articles.
1. R. Acar, C. R. Vogel.Analysis of bounded variation penalty methods for ill-posed problems, Inverse Problems, 10 (1994), 1217-1229.
2. S. T. Acton.Multigrid anisotropic diffusion, IEEE Transactions on Image Processing: A Publication of the IEEE Signal Processing Society, 7 (1998), 280-291.
3. X. Bresson, T. F. Chan.Fast dual minimization of the vectorial total variation norm and applications to color image processing, Inverse Probl. Imaging, 2 (2008), 455-484.
4. C. Brito-Loeza, K. Chen.On high-order denoising models and fast algorithms for vector-valued images, IEEE Trans. Image Process., 19 (2010), 1518-1527.
5. A. Chambolle.An algorithm for total variation minimization and applications, J. Math. Imaging Vision, 20 (2004), 89-97.
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献