Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/98057
Title: Domain decomposition methods with graph cuts algorithms for total variation minimization
Authors: Duan, Yuping
Tai, Xue Cheng
Issue Date: 2011
Source: Duan, Y., & Tai, X.-C. (2012). Domain decomposition methods with graph cuts algorithms for total variation minimization. Advances in Computational Mathematics, 36(2), 175-199.
Series/Report no.: Advances in computational mathematics
Abstract: Recently, graph cuts algorithms have been used to solve variational image restoration problems, especially for noise removal and segmentation. Compared to time-marching PDE methods, graph cuts based methods are more efficient and able to obtain the global minimizer. However, for high resolution and large-scale images, the cost of both memory and computational time increases dramatically. In this paper, we combine the domain decomposition method and the graph cuts algorithm for solving the total variation minimizations with L1 and L2 fidelity term. Numerous numerical experiments on large-scale data demonstrate the proposed algorithm yield good results in terms of computational time and memory usage.
URI: https://hdl.handle.net/10356/98057
http://hdl.handle.net/10220/12328
DOI: http://dx.doi.org/10.1007/s10444-011-9213-4
Rights: © 2011 Springer Science+Business Media, LLC.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SPMS Journal Articles

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