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A PARALLEL DOMAIN DECOMPOSITION ALGORITHM FOR LARGE SCALE IMAGE DENOISING
Chen, Rongliang1; Huang, Jizu2; Cai, Xiao-Chuan3
2019-12-01
Source PublicationINVERSE PROBLEMS AND IMAGING
ISSN1930-8337
Volume13Issue:6Pages:1259-1282
AbstractTotal variation denoising (TVD) is an effective technique for image denoising, in particular, for recovering blocky, discontinuous images from noisy background. The problem is formulated as an optimization problem in the space of bounded variation functions, and the solution is obtained by solving the associated Euler-Lagrange equation defined on the domain occupied by the entire image. The method offers high quality results, but is computationally expensive for large images, especially for three-dimensional problems. In this paper, we introduce a highly parallel version of the algorithm which formulates the problem as multiple overlapping, but independent, optimization problems, and each is defined on a portion of the image domain. This approach is similar to the overlapping Schwarz type domain decomposition method, but is non-iterative, for solving partial differential equations, and is highly scalable, without using any coarse grids, for parallel computers with a large number of processors. We show by a theory and also by some two- and three-dimensional numerical experiments that the new approach has similar numerical accuracy as the classical TVD approach, but is much more efficient on parallel computers.
KeywordImage denoising total variation overlapping domain decomposition Newton-Krylov-Schwarz parallel processing
DOI10.3934/ipi.2019055
Language英语
Funding ProjectNational Key RD Program[2016YFB0200601] ; Shenzhen grant[JCYJ20170307165328836] ; Shenzhen grant[ZDSYS201703031711426] ; Shenzhen grant[JCYJ20160331193229720] ; NSFC[61531166003]
WOS Research AreaMathematics ; Physics
WOS SubjectMathematics, Applied ; Physics, Mathematical
WOS IDWOS:000489305500005
PublisherAMER INST MATHEMATICAL SCIENCES-AIMS
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/35925
Collection计算数学与科学工程计算研究所
Corresponding AuthorCai, Xiao-Chuan
Affiliation1.Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Guangdong, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, ICMSEC, LSEC, Beijing 100190, Peoples R China
3.Univ Colorado, Dept Comp Sci, Boulder, CO 80309 USA
Recommended Citation
GB/T 7714
Chen, Rongliang,Huang, Jizu,Cai, Xiao-Chuan. A PARALLEL DOMAIN DECOMPOSITION ALGORITHM FOR LARGE SCALE IMAGE DENOISING[J]. INVERSE PROBLEMS AND IMAGING,2019,13(6):1259-1282.
APA Chen, Rongliang,Huang, Jizu,&Cai, Xiao-Chuan.(2019).A PARALLEL DOMAIN DECOMPOSITION ALGORITHM FOR LARGE SCALE IMAGE DENOISING.INVERSE PROBLEMS AND IMAGING,13(6),1259-1282.
MLA Chen, Rongliang,et al."A PARALLEL DOMAIN DECOMPOSITION ALGORITHM FOR LARGE SCALE IMAGE DENOISING".INVERSE PROBLEMS AND IMAGING 13.6(2019):1259-1282.
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