메뉴 건너뛰기




Volumn 44, Issue 6, 2011, Pages 1312-1326

Linearized proximal alternating minimization algorithm for motion deblurring by nonlocal regularization

Author keywords

Alternating minimization; Convex optimization; Deconvolution; Motion deblurring; Nonlocal; Regularization; Total variation

Indexed keywords

ALTERNATING MINIMIZATION; MOTION DEBLURRING; NONLOCAL; REGULARIZATION; TOTAL VARIATION;

EID: 79551523372     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2010.12.013     Document Type: Article
Times cited : (29)

References (40)
  • 2
    • 49249099286 scopus 로고    scopus 로고
    • High-quality motion deblurring from a single image
    • Q. Shan, J. Jia, and A. Agarwala High-quality motion deblurring from a single image ACM Trans. Graphics 27 2008 73:1 73:10
    • (2008) ACM Trans. Graphics , vol.27 , pp. 731-7310
    • Shan, Q.1    Jia, J.2    Agarwala, A.3
  • 3
    • 74549163652 scopus 로고    scopus 로고
    • Multi-scale blind motion deblurring using local minimum
    • C. Wang, L. Sun, Z.Y. Chen, J.W. Zhang, and S.Q. Yang Multi-scale blind motion deblurring using local minimum Inverse Probl. 26 2010 015003
    • (2010) Inverse Probl. , vol.26 , pp. 015003
    • Wang, C.1    Sun, L.2    Chen, Z.Y.3    Zhang, J.W.4    Yang, S.Q.5
  • 6
    • 44049111982 scopus 로고
    • Nonlinear total variation based noise removal algorithms
    • L. Rudin, S. Osher, and E. Fatemi Nonlinear total variation based noise removal algorithms Physica D 60 1992 259 268
    • (1992) Physica D , vol.60 , pp. 259-268
    • Rudin, L.1    Osher, S.2    Fatemi, E.3
  • 7
    • 67349204846 scopus 로고    scopus 로고
    • Adaptive total variation image deblurring: A majorization-minimization approach
    • J.P. Oliveira, J.M. Bioucas-Dias, and M.A.T. Figueiredo Adaptive total variation image deblurring: a majorization-minimization approach Signal Process. 89 2009 1683 1693
    • (2009) Signal Process. , vol.89 , pp. 1683-1693
    • Oliveira, J.P.1    Bioucas-Dias, J.M.2    Figueiredo, M.A.T.3
  • 8
    • 33746217159 scopus 로고    scopus 로고
    • Variational denoising of partly textured images by spatially varying constraints
    • G. Gilboa, N. Sochen, and Y.Y. Zeevi Variational denoising of partly textured images by spatially varying constraints IEEE Trans. Image Process. 15 2006 2281 2289
    • (2006) IEEE Trans. Image Process. , vol.15 , pp. 2281-2289
    • Gilboa, G.1    Sochen, N.2    Zeevi, Y.Y.3
  • 10
    • 41549098470 scopus 로고    scopus 로고
    • Nonlocal linear image regularization and supervised segmentation
    • G. Gilboa, and S. Osher Nonlocal linear image regularization and supervised segmentation Multiscale Model. Simul. 6 2007 595 630
    • (2007) Multiscale Model. Simul. , vol.6 , pp. 595-630
    • Gilboa, G.1    Osher, S.2
  • 11
    • 33845467001 scopus 로고    scopus 로고
    • Deblurring and denoising of images by nonlocal functionals
    • S. Kindermann, S. Osher, and P.W. Jones Deblurring and denoising of images by nonlocal functionals Multiscale Model. Simul. 4 2005 1091 1115
    • (2005) Multiscale Model. Simul. , vol.4 , pp. 1091-1115
    • Kindermann, S.1    Osher, S.2    Jones, P.W.3
  • 13
    • 78149463074 scopus 로고    scopus 로고
    • Bregmanized nonlocal regularization for deconvolution and sparse reconstruction
    • X. Zhang, M. Burger, X. Bresson, and S. Osher Bregmanized nonlocal regularization for deconvolution and sparse reconstruction SIAM J. Imaging Sci. 3 2010 253 276
    • (2010) SIAM J. Imaging Sci. , vol.3 , pp. 253-276
    • Zhang, X.1    Burger, M.2    Bresson, X.3    Osher, S.4
  • 15
    • 84864949823 scopus 로고    scopus 로고
    • Nonlocal unsupervised variational image segmentation models
    • X. Bresson, T.F. Chan, Nonlocal unsupervised variational image segmentation models, UCLA Cam-Report, 2008.
    • (2008) UCLA Cam-Report
    • Bresson, X.1    Chan, T.F.2
  • 16
    • 45949105032 scopus 로고    scopus 로고
    • Nonlocal discrete regularization on weighted graphs: A framework for image and manifold processing
    • A. Elmoataz, O. Lezoray, and S. Bougleux Nonlocal discrete regularization on weighted graphs: a framework for image and manifold processing IEEE Trans. Image Process. 17 2008 1047 1060
    • (2008) IEEE Trans. Image Process. , vol.17 , pp. 1047-1060
    • Elmoataz, A.1    Lezoray, O.2    Bougleux, S.3
  • 17
    • 57049132103 scopus 로고    scopus 로고
    • Nonlocal operators with applications to image processing
    • G. Gilboa, and S. Osher Nonlocal operators with applications to image processing Multiscale Model. Simul. 7 2008 1005 1028
    • (2008) Multiscale Model. Simul. , vol.7 , pp. 1005-1028
    • Gilboa, G.1    Osher, S.2
  • 18
    • 85012251675 scopus 로고    scopus 로고
    • A new alternating minimization algorithm for total variation image reconstruction
    • Y. Wang, J. Yang, W. Yin, and Y. Zhang A new alternating minimization algorithm for total variation image reconstruction SIAM J. Imaging Sci. 1 2008 248 272
    • (2008) SIAM J. Imaging Sci. , vol.1 , pp. 248-272
    • Wang, Y.1    Yang, J.2    Yin, W.3    Zhang, Y.4
  • 20
    • 77952428549 scopus 로고    scopus 로고
    • An efficient primal-dual hybrid gradient algorithm for total variation image restoration
    • M. Zhu, T. Chan, An efficient primaldual hybrid gradient algorithm for total variation image restoration, UCLA CAM-Report, 2008.
    • (2008) UCLA CAM-Report
    • Zhu, M.1    Chan, T.2
  • 21
    • 0026077016 scopus 로고
    • Applications of a splitting algorithm to decomposition in convex programming and variational inequalities
    • P. Tseng Applications of a splitting algorithm to decomposition in convex programming and variational inequalities SIAM J. Control Optim. 29 1991 119 138
    • (1991) SIAM J. Control Optim. , vol.29 , pp. 119-138
    • Tseng, P.1
  • 23
    • 25444446893 scopus 로고    scopus 로고
    • Simultaneous total variation image inpainting and blind deconvolution
    • T.F. Chan, A.M. Yip, and F.E. Park Simultaneous total variation image inpainting and blind deconvolution Int. J. Imaging Syst. Technol. 15 2005 92 102
    • (2005) Int. J. Imaging Syst. Technol. , vol.15 , pp. 92-102
    • Chan, T.F.1    Yip, A.M.2    Park, F.E.3
  • 24
    • 13744259707 scopus 로고    scopus 로고
    • Anti-reflective boundary conditions and re-blurring
    • M. Donatelli, and S. Capizzano Anti-reflective boundary conditions and re-blurring Inverse Probl. 22 2005 169 182
    • (2005) Inverse Probl. , vol.22 , pp. 169-182
    • Donatelli, M.1    Capizzano, S.2
  • 27
    • 84969334819 scopus 로고    scopus 로고
    • The split Bregman method for L1 regularized problems
    • T. Goldstein, and S. Osher The split Bregman method for L1 regularized problems SIAM J. Imaging Sci. 2 2009 323 343
    • (2009) SIAM J. Imaging Sci. , vol.2 , pp. 323-343
    • Goldstein, T.1    Osher, S.2
  • 28
    • 76149085420 scopus 로고    scopus 로고
    • A general framework for a class of first order primal-dual algorithms for TV minimization
    • E. Esser, X. Zhang, T. Chan, A general framework for a class of first order primaldual algorithms for TV minimization, UCLA CAM-Report, 2009.
    • (2009) UCLA CAM-Report
    • Esser, E.1    Zhang, X.2    Chan, T.3
  • 29
    • 77249161628 scopus 로고    scopus 로고
    • A unified primal-dual algorithm framework based on Bregman iteration
    • X. Zhang, M. Burger, S. Osher, A unified primaldual algorithm framework based on Bregman iteration, UCLA CAM-Report, 2009.
    • (2009) UCLA CAM-Report
    • Zhang, X.1    Burger, M.2    Osher, S.3
  • 30
    • 79551532991 scopus 로고    scopus 로고
    • Applications of Lagrangian-based alternating direction methods and connections to split-Bregman
    • E. Esser, Applications of Lagrangian-based alternating direction methods and connections to split-Bregman, UCLA CAM-Report, 2009.
    • (2009) UCLA CAM-Report
    • Esser, E.1
  • 32
    • 78650834156 scopus 로고    scopus 로고
    • Augmented Lagrangian method dual methods and split Bregman iterations for ROF, vectorial TV and higher order models
    • C. Wu, and X.-C. Tai Augmented Lagrangian method dual methods and split Bregman iterations for ROF, vectorial TV and higher order models SIAM J. Imaging Sci. 3 2010 300 339
    • (2010) SIAM J. Imaging Sci. , vol.3 , pp. 300-339
    • Wu, C.1    Tai, X.-C.2
  • 33
    • 80052211668 scopus 로고    scopus 로고
    • Operator splitting, Bregman methods and frame shrinkage in image processing
    • in press, doi: 10.1007/s11263-010-0357-3
    • S. Setzer, Operator splitting, Bregman methods and frame shrinkage in image processing, Int. J. Comput. Vision, in press, doi: 10.1007/s11263-010- 0357-3.
    • Int. J. Comput. Vision
    • Setzer, S.1
  • 35
    • 1242352408 scopus 로고    scopus 로고
    • An algorithm for total variation minimization and applications
    • A. Chambolle An algorithm for total variation minimization and applications J. Math. Imaging Vision 20 2004 89 97
    • (2004) J. Math. Imaging Vision , vol.20 , pp. 89-97
    • Chambolle, A.1
  • 36
    • 70350593691 scopus 로고    scopus 로고
    • Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems
    • A. Beck, and M. Teboulle Fast gradient-based algorithms for constrained total variation image denoising and deblurring problems IEEE Trans. Image Process. 18 2009 2419 2434
    • (2009) IEEE Trans. Image Process. , vol.18 , pp. 2419-2434
    • Beck, A.1    Teboulle, M.2
  • 38
    • 30844438177 scopus 로고    scopus 로고
    • Signal recovery by proximal forward-backward splitting
    • P. Combettes, and W. Wajs Signal recovery by proximal forward-backward splitting Multiscale Model. Simul. 4 2005 1168 1200
    • (2005) Multiscale Model. Simul. , vol.4 , pp. 1168-1200
    • Combettes, P.1    Wajs, W.2
  • 39
    • 0242462717 scopus 로고    scopus 로고
    • A new inexact alteration directions method for monotone variational inequalities
    • B. He, L.Z. Liao, D. Han, and H. Yang A new inexact alteration directions method for monotone variational inequalities Math. Program. 92 2002 103 118
    • (2002) Math. Program. , vol.92 , pp. 103-118
    • He, B.1    Liao, L.Z.2    Han, D.3    Yang, H.4
  • 40
    • 69649095451 scopus 로고    scopus 로고
    • Fixed-point continuation for L1-minimization: Methodology and convergence
    • E.T. Hale, W. Yin, and Y. Zhang Fixed-point continuation for L1-minimization: methodology and convergence SIAM J. Optim. 19 2008 1107 1130
    • (2008) SIAM J. Optim. , vol.19 , pp. 1107-1130
    • Hale, E.T.1    Yin, W.2    Zhang, Y.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.