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Volumn 8, Issue 2, 2015, Pages 1187-1219

Boosting of image denoising algorithms

Author keywords

Boosting; Denoising; Graph Laplacian; Graph theory; Image restoration; K SVD; Regularization; Sparse representation

Indexed keywords

ALGORITHMS; GRAPH THEORY; IMAGE RECONSTRUCTION; LAPLACE TRANSFORMS; RESTORATION; SYSTEMS ENGINEERING;

EID: 84936764429     PISSN: None     EISSN: 19364954     Source Type: Journal    
DOI: 10.1137/140990978     Document Type: Article
Times cited : (150)

References (53)
  • 1
    • 33750383209 scopus 로고    scopus 로고
    • The K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representation
    • M. Aharon, M. Elad, and A. Bruckstein, The K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representation, IEEE Trans. Signal Process., 54 (2006), pp. 4311-4322.
    • (2006) IEEE Trans. Signal Process , vol.54 , pp. 4311-4322
    • Aharon, M.1    Elad, M.2    Bruckstein, A.3
  • 2
    • 67349199594 scopus 로고    scopus 로고
    • Local and nonlocal discrete regularization on weighted graphs for image and mesh processing
    • S. Bougleux, A. Elmoataz, and M. Melkemi, Local and nonlocal discrete regularization on weighted graphs for image and mesh processing, Internat. J. Comput. Vis., 84 (2009), pp. 220-236.
    • (2009) Internat. J. Comput. Vis , vol.84 , pp. 220-236
    • Bougleux, S.1    Elmoataz, A.2    Melkemi, M.3
  • 3
    • 80051762104 scopus 로고    scopus 로고
    • Distributed optimization and statistical learning via the alternating direction method of multipliers
    • S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein, Distributed optimization and statistical learning via the alternating direction method of multipliers, Found. Trends Machine Learning, 3 (2011), pp. 1-122.
    • (2011) Found. Trends Machine Learning , vol.3 , pp. 1-122
    • Boyd, S.1    Parikh, N.2    Chu, E.3    Peleato, B.4    Eckstein, J.5
  • 4
    • 49949144765 scopus 로고
    • The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming
    • L. M. Bregman, The relaxation method of finding the common point of convex sets and its application to the solution of problems in convex programming, USSR Comput. Math. Math. Phys., 7 (1967), pp. 200-217.
    • (1967) USSR Comput. Math. Math. Phys , vol.7 , pp. 200-217
    • Bregman, L.M.1
  • 5
    • 59749104367 scopus 로고    scopus 로고
    • From sparse solutions of systems of equations to sparse modeling of signals and images
    • A. M. Bruckstein, D. L. Donoho, and M. Elad, From sparse solutions of systems of equations to sparse modeling of signals and images, SIAM Rev., 51 (2009), pp. 34-81.
    • (2009) SIAM Rev , vol.51 , pp. 34-81
    • Bruckstein, A.M.1    Donoho, D.L.2    Elad, M.3
  • 6
    • 33645653318 scopus 로고    scopus 로고
    • A review of image denoising algorithms, with a new one
    • A. Buades, B. Coll, and J. M. Morel, A review of image denoising algorithms, with a new one, Multiscale Model. Simul., 4 (2005), pp. 490-530.
    • (2005) Multiscale Model. Simul , vol.4 , pp. 490-530
    • Buades, A.1    Coll, B.2    Morel, J.M.3
  • 8
    • 0043245810 scopus 로고    scopus 로고
    • Boosting with the l2 loss: Regression and classification
    • P. Bühlmann and B. Yu, Boosting with the l2 loss: Regression and classification, J. Amer. Statist. Assoc., 98 (2003), pp. 324-339.
    • (2003) J. Amer. Statist. Assoc , vol.98 , pp. 324-339
    • Bühlmann, P.1    Yu, B.2
  • 11
    • 84859089425 scopus 로고    scopus 로고
    • Patch-based near-optimal image denoising
    • P. Chatterjee and P. Milanfar, Patch-based near-optimal image denoising, IEEE Trans. Image Process., 21 (2012), pp. 1635-1649.
    • (2012) IEEE Trans. Image Process , vol.21 , pp. 1635-1649
    • Chatterjee, P.1    Milanfar, P.2
  • 13
    • 34547760736 scopus 로고    scopus 로고
    • Image denoising by sparse 3-D transformdomain collaborative filtering
    • K. Dabov, A. Foi, V. Katkovnik, and K. Egiazarian, Image denoising by sparse 3-D transformdomain collaborative filtering, IEEE Trans. Image Process., 16 (2007), pp. 2080-2095.
    • (2007) IEEE Trans. Image Process , vol.16 , pp. 2080-2095
    • Dabov, K.1    Foi, A.2    Katkovnik, V.3    Egiazarian, K.4
  • 15
    • 33751379736 scopus 로고    scopus 로고
    • Image denoising via sparse and redundant representations over learned dictionaries
    • M. Elad and M. Aharon, Image denoising via sparse and redundant representations over learned dictionaries, IEEE Trans. Image Process., 15 (2006), pp. 3736-3745.
    • (2006) IEEE Trans. Image Process , vol.15 , pp. 3736-3745
    • Elad, M.1    Aharon, M.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), pp. 1047-1060.
    • (2008) IEEE Trans. Image Process , vol.17 , pp. 1047-1060
    • Elmoataz, A.1    Lezoray, O.2    Bougleux, S.3
  • 19
    • 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), pp. 595-630.
    • (2007) Multiscale Model. Simul , vol.6 , pp. 595-630
    • Gilboa, G.1    Osher, S.2
  • 20
    • 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), pp. 1005-1028.
    • (2008) Multiscale Model. Simul , vol.7 , pp. 1005-1028
    • Gilboa, G.1    Osher, S.2
  • 21
    • 84925004615 scopus 로고    scopus 로고
    • Symmetric smoothing filters from global consistency constraints
    • S. M. Haque, G. Pai, and V. M. Govindu, Symmetric smoothing filters from global consistency constraints, IEEE Trans. Image Process., 24 (2014), pp. 1536-1548.
    • (2014) IEEE Trans. Image Process , vol.24 , pp. 1536-1548
    • Haque, S.M.1    Pai, G.2    Govindu, V.M.3
  • 22
    • 0004151494 scopus 로고    scopus 로고
    • Cambridge University Press, Cambridge, UK
    • R. A. Horn and C. R. Johnson, Matrix Analysis, Cambridge University Press, Cambridge, UK, 2012.
    • (2012) Matrix Analysis
    • Horn, R.A.1    Johnson, C.R.2
  • 24
    • 84908432911 scopus 로고    scopus 로고
    • A general framework for regularized, similarity-based image restoration
    • A. Kheradmand and P. Milanfar, A general framework for regularized, similarity-based image restoration, IEEE Trans. Image Process., 23 (2014), pp. 5136-5151.
    • (2014) IEEE Trans. Image Process , vol.23 , pp. 5136-5151
    • Kheradmand, A.1    Milanfar, P.2
  • 25
    • 84880302753 scopus 로고    scopus 로고
    • A fast algorithm for matrix balancing
    • P. A. Knight and D. Ruiz, A fast algorithm for matrix balancing, IMA J. Numer. Anal., 33 (2013), pp. 1029-1047.
    • (2013) IMA J. Numer. Anal , vol.33 , pp. 1029-1047
    • Knight, P.A.1    Ruiz, D.2
  • 26
    • 84903118256 scopus 로고    scopus 로고
    • Implementation of the "Non-Local Bayes" (NL-Bayes) Image Denoising Algorithm
    • M. Lebrun, A. Buades, and J.-M. Morel, Implementation of the "Non-Local Bayes" (NL-Bayes) Image Denoising Algorithm, Image Processing On Line, 3 (2013), pp. 1-42. http://www.ipol.im/ pub/art/2013/16/article.pdf.
    • (2013) Image Processing On Line , vol.3 , pp. 1-42
    • Lebrun, M.1    Buades, A.2    Morel, J.-M.3
  • 29
    • 84897742684 scopus 로고    scopus 로고
    • Progressive image denoising through hybrid graph Laplacian regularization: A unified framework
    • X. Liu, D. Zhai, D. Zhao, G. Zhai, and W. Gao, Progressive image denoising through hybrid graph Laplacian regularization: A unified framework, IEEE Trans. Image Process., 23 (2014), pp. 1491-1503.
    • (2014) IEEE Trans. Image Process , vol.23 , pp. 1491-1503
    • Liu, X.1    Zhai, D.2    Zhao, D.3    Zhai, G.4    Gao, W.5
  • 30
    • 84892994454 scopus 로고    scopus 로고
    • Perturbation of the eigenvectors of the graph Laplacian: Application to image denoising
    • F. G. Meyer and X. Shen, Perturbation of the eigenvectors of the graph Laplacian: Application to image denoising, Appl. Comput. Harmon. Anal., 36 (2014), pp. 326-334.
    • (2014) Appl. Comput. Harmon. Anal , vol.36 , pp. 326-334
    • Meyer, F.G.1    Shen, X.2
  • 31
    • 85032773691 scopus 로고    scopus 로고
    • A tour of modern image filtering: New insights and methods, both practical and theoretical
    • P. Milanfar, A tour of modern image filtering: New insights and methods, both practical and theoretical, IEEE Signal Process. Mag., 30 (2013), pp. 106-128.
    • (2013) IEEE Signal Process. Mag , vol.30 , pp. 106-128
    • Milanfar, P.1
  • 32
    • 19844370110 scopus 로고    scopus 로고
    • An iterative regularization method for total variation-based image restoration
    • S. Osher, M. Burger, D. Goldfarb, J. Xu, and W. Yin, An iterative regularization method for total variation-based image restoration, Multiscale Model. Simul., 4 (2005), pp. 460-489.
    • (2005) Multiscale Model. Simul , vol.4 , pp. 460-489
    • Osher, S.1    Burger, M.2    Goldfarb, D.3    Xu, J.4    Yin, W.5
  • 34
    • 58149144703 scopus 로고    scopus 로고
    • Generalizing the nonlocal-means to superresolution reconstruction
    • M. Protter, M. Elad, H. Takeda, and P. Milanfar, Generalizing the nonlocal-means to superresolution reconstruction, IEEE Trans. Image Process., 18 (2009), pp. 36-51.
    • (2009) IEEE Trans. Image Process , vol.18 , pp. 36-51
    • Protter, M.1    Elad, M.2    Takeda, H.3    Milanfar, P.4
  • 35
    • 84877883372 scopus 로고    scopus 로고
    • Image processing using smooth ordering of its patches
    • I. Ram, M. Elad, and I. Cohen, Image processing using smooth ordering of its patches, IEEE Trans. Image Process., 22 (2013), pp. 2764-2774.
    • (2013) IEEE Trans. Image Process , vol.22 , pp. 2764-2774
    • Ram, I.1    Elad, M.2    Cohen, I.3
  • 38
    • 84903171441 scopus 로고    scopus 로고
    • Single image interpolation via adaptive nonlocal sparsity-based modeling
    • Y. Romano, M. Protter, and M. Elad, Single image interpolation via adaptive nonlocal sparsity-based modeling, IEEE Trans. Image Process., 23 (2014), pp. 3085-3098.
    • (2014) IEEE Trans. Image Process , vol.23 , pp. 3085-3098
    • Romano, Y.1    Protter, M.2    Elad, M.3
  • 39
    • 44049111982 scopus 로고
    • Nonlinear total variation based noise removal algorithms
    • L. I. Rudin, S. Osher, and E. Fatemi, Nonlinear total variation based noise removal algorithms, Phys. D, 60 (1992), pp. 259-268.
    • (1992) Phys. D , vol.60 , pp. 259-268
    • Rudin, L.I.1    Osher, S.2    Fatemi, E.3
  • 41
    • 85032751310 scopus 로고    scopus 로고
    • The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains
    • D. I. Shuman, S. K. Narang, P. Frossard, A. Ortega, and P. Vandergheynst, The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains, IEEE Signal Process. Mag., 30 (2013), pp. 83-98.
    • (2013) IEEE Signal Process. Mag , vol.30 , pp. 83-98
    • Shuman, D.I.1    Narang, S.K.2    Frossard, P.3    Ortega, A.4    Vandergheynst, P.5
  • 42
    • 84870874964 scopus 로고    scopus 로고
    • Improving dictionary learning: Multiple dictionary updates and coefficient reuse
    • L. N. Smith and M. Elad, Improving dictionary learning: Multiple dictionary updates and coefficient reuse, Signal Process. Lett., 20 (2013), pp. 79-82.
    • (2013) Signal Process. Lett , vol.20 , pp. 79-82
    • Smith, L.N.1    Elad, M.2
  • 44
    • 50949129496 scopus 로고    scopus 로고
    • Regularization on graphs with function-adapted diffusion processes
    • A. D. Szlam, M. Maggioni, and R. R. Coifman, Regularization on graphs with function-adapted diffusion processes, J. Machine Learning Res., 9 (2008), pp. 1711-1739.
    • (2008) J. Machine Learning Res , vol.9 , pp. 1711-1739
    • Szlam, A.D.1    Maggioni, M.2    Coifman, R.R.3
  • 46
    • 84873694228 scopus 로고    scopus 로고
    • How to SAIF-ly boost denoising performance
    • H. Talebi, X. Zhu, and P. Milanfar, How to SAIF-ly boost denoising performance, IEEE Trans. Image Process., 22 (2013), pp. 1470-1485.
    • (2013) IEEE Trans. Image Process , vol.22 , pp. 1470-1485
    • Talebi, H.1    Zhu, X.2    Milanfar, P.3
  • 48
    • 77952743135 scopus 로고    scopus 로고
    • Computational methods for sparse solution of linear inverse problems
    • J. A. Tropp and S. J. Wright, Computational methods for sparse solution of linear inverse problems, Proc. IEEE, 98 (2010), pp. 948-958.
    • (2010) Proc. IEEE , vol.98 , pp. 948-958
    • Tropp, J.A.1    Wright, S.J.2
  • 50
    • 34548583274 scopus 로고    scopus 로고
    • A tutorial on spectral clustering
    • U. Von Luxburg, A tutorial on spectral clustering, Statist. Comput., 17 (2007), pp. 395-416.
    • (2007) Statist. Comput , vol.17 , pp. 395-416
    • Von Luxburg, U.1
  • 51
    • 84860189704 scopus 로고    scopus 로고
    • Solving inverse problems with piecewise linear estimators: From Gaussian mixture models to structured sparsity
    • G. Yu, G. Sapiro, and S. Mallat, Solving inverse problems with piecewise linear estimators: From Gaussian mixture models to structured sparsity, IEEE Trans. Image Process., 21 (2012), pp. 2481- 2499.
    • (2012) IEEE Trans. Image Process , vol.21 , pp. 2481-2499
    • Yu, G.1    Sapiro, G.2    Mallat, S.3


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