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Volumn 23, Issue 5, 2012, Pages 753-766

An augmented Lagrangian approach to general dictionary learning for image denoising

Author keywords

Accelerated technique; Augmented Lagrangian; Bregman iterative method; Dictionary learning; Gaussian noise removal; Impulse noise removal; Iteratively Reweighted Norm; Sparse representation

Indexed keywords

ACCELERATED TECHNIQUE; AUGMENTED LAGRANGIANS; DICTIONARY LEARNING; ITERATIVELY REWEIGHTED NORM; SPARSE REPRESENTATION;

EID: 84860866172     PISSN: 10473203     EISSN: 10959076     Source Type: Journal    
DOI: 10.1016/j.jvcir.2012.04.003     Document Type: Article
Times cited : (29)

References (38)
  • 1
    • 33750383209 scopus 로고    scopus 로고
    • The K-SVD: An algorithm for designing of overcomplete dictionaries for sparse representations
    • M. Aharon, M. Elad, and A.M. Bruckstein The K-SVD: an algorithm for designing of overcomplete dictionaries for sparse representations IEEE Trans. Signal Process. 54 11 2006 4311 4322
    • (2006) IEEE Trans. Signal Process. , vol.54 , Issue.11 , pp. 4311-4322
    • Aharon, M.1    Elad, M.2    Bruckstein, A.M.3
  • 2
    • 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 12 2006 3736 3745
    • (2006) IEEE Trans. Image Process. , vol.15 , Issue.12 , pp. 3736-3745
    • Elad, M.1    Aharon, M.2
  • 3
    • 67349251766 scopus 로고    scopus 로고
    • Sparse and redundant modeling of image content using an image-signature-dictionary
    • M. Aharon, and M. Elad Sparse and redundant modeling of image content using an image-signature-dictionary SIAM J. Imaging Sci. 1 2008 228 247
    • (2008) SIAM J. Imaging Sci. , vol.1 , pp. 228-247
    • Aharon, M.1    Elad, M.2
  • 4
    • 5444237123 scopus 로고    scopus 로고
    • Greed is good: Algorithmic results for sparse approximation
    • J.A. Tropp Greed is good: algorithmic results for sparse approximation IEEE Trans. Inf. Theor. 50 10 2004 2231 2242
    • (2004) IEEE Trans. Inf. Theor. , vol.50 , Issue.10 , pp. 2231-2242
    • Tropp, J.A.1
  • 5
    • 68949221380 scopus 로고    scopus 로고
    • Efficient implementation of the K-SVD algorithm using batch orthogonal matching pursuit
    • R. Rubinstein, M. Zibulevsky, M. Elad, Efficient implementation of the K-SVD algorithm using batch orthogonal matching pursuit, Technical Report - CS Technion, 2008.
    • (2008) Technical Report - CS Technion
    • Rubinstein, R.1    Zibulevsky, M.2    Elad, M.3
  • 7
    • 0035273106 scopus 로고    scopus 로고
    • Atomic decomposition by basis pursuit
    • S.S. Chen, D.L. Donoho, and M.A. Saunders Atomic decomposition by basis pursuit SIAM Rev. 43 1 2001 129 159
    • (2001) SIAM Rev. , vol.43 , Issue.1 , pp. 129-159
    • Chen, S.S.1    Donoho, D.L.2    Saunders, M.A.3
  • 8
    • 0031102203 scopus 로고    scopus 로고
    • Sparse signal reconstruction from limited data using FOCUSS: A re-weighted minimum norm algorithm
    • I. Gorodnitsky, and B. Rao Sparse signal reconstruction from limited data using FOCUSS: a re-weighted minimum norm algorithm IEEE Trans. Signal Process. 45 3 1997 600 616
    • (1997) IEEE Trans. Signal Process. , vol.45 , Issue.3 , pp. 600-616
    • Gorodnitsky, I.1    Rao, B.2
  • 9
    • 0032712352 scopus 로고    scopus 로고
    • An affine scaling methodology for best basis selection
    • B.D. Rao, and K.K-. Delgado An affine scaling methodology for best basis selection IEEE Trans. Signal Process. 47 1 1999 187 200
    • (1999) IEEE Trans. Signal Process. , vol.47 , Issue.1 , pp. 187-200
    • Rao, B.D.1    Delgado, K.K.2
  • 11
    • 0030779611 scopus 로고    scopus 로고
    • Sparse coding with an overcomplete basis set: A strategy employed by V1?
    • B. Olshausen, and D. Field Sparse coding with an overcomplete basis set: a strategy employed by V1? Vis. Res. 37 23 1997 3311 3325
    • (1997) Vis. Res. , vol.37 , Issue.23 , pp. 3311-3325
    • Olshausen, B.1    Field, D.2
  • 12
    • 0029938380 scopus 로고    scopus 로고
    • Emergence of simple-cell receptive field properties by learning a sparse code for natural images
    • B.A. Olshausen, and D.J. Field Emergence of simple-cell receptive field properties by learning a sparse code for natural images Nature 381 1996 607 609
    • (1996) Nature , vol.381 , pp. 607-609
    • Olshausen, B.A.1    Field, D.J.2
  • 14
    • 0032625443 scopus 로고    scopus 로고
    • Frame based signal compression using method of optimal directions (MOD)
    • K. Engan, S.O. Aase, J.H. Husoy, Frame based signal compression using method of optimal directions (MOD), in: Proceedings of ISCS, 1999.
    • (1999) Proceedings of ISCS
    • Engan, K.1    Aase, S.O.2    Husoy, J.H.3
  • 15
    • 71149119964 scopus 로고    scopus 로고
    • Online dictionary learning for sparse coding
    • J. Mairal, F. Bach, J. Ponce, G. Sapiro, Online dictionary learning for sparse coding. ICML, 2009.
    • (2009) ICML
    • Mairal, J.1    Bach, F.2    Ponce, J.3    Sapiro, G.4
  • 18
    • 30844445842 scopus 로고    scopus 로고
    • Algorithms for simultaneous sparse approximation
    • J.A. Tropp Algorithms for simultaneous sparse approximation Signal Process. 86 2006 572 602
    • (2006) Signal Process. , vol.86 , pp. 572-602
    • Tropp, J.A.1
  • 20
    • 77951169269 scopus 로고    scopus 로고
    • Bayesian orthogonal component analysis for sparse representation
    • N. Dobigeon, and J.Y. Tourneret Bayesian orthogonal component analysis for sparse representation IEEE Trans. Signal Process. 58 5 2010 2675 2685
    • (2010) IEEE Trans. Signal Process. , vol.58 , Issue.5 , pp. 2675-2685
    • Dobigeon, N.1    Tourneret, J.Y.2
  • 22
    • 84861651251 scopus 로고    scopus 로고
    • An augmented Lagrangian multi-scale dictionary learning algorithm
    • 10.1186/1687-6180-2011-58
    • Q. Liu, J. Luo, S. Wang, M. Xiao, and M. Ye An augmented Lagrangian multi-scale dictionary learning algorithm EURASIP J. Adv. Signal Process. 2011 58 2011 10.1186/1687-6180-2011-58
    • (2011) EURASIP J. Adv. Signal Process. , vol.2011 , Issue.58
    • Liu, Q.1    Luo, J.2    Wang, S.3    Xiao, M.4    Ye, M.5
  • 23
    • 63049122761 scopus 로고    scopus 로고
    • A predual proximal point algorithm solving a non-negative basis pursuit denoising model
    • F. Malgouyres, and T. Zeng A predual proximal point algorithm solving a non-negative basis pursuit denoising model Int. J. Comput. Vis. 83 3 2009 294 311
    • (2009) Int. J. Comput. Vis. , vol.83 , Issue.3 , pp. 294-311
    • Malgouyres, F.1    Zeng, T.2
  • 24
  • 25
    • 84977895355 scopus 로고    scopus 로고
    • Bregman iterative algorithms for l1-minimization with applications to compressed sensing
    • W. Yin, S. Osher, D. Goldfarb, and J. Darbon Bregman iterative algorithms for l1-minimization with applications to compressed sensing SIAM J. Imaging Sci. 1 2008 142 168
    • (2008) SIAM J. Imaging Sci. , vol.1 , pp. 142-168
    • Yin, W.1    Osher, S.2    Goldfarb, D.3    Darbon, J.4
  • 26
    • 59649097565 scopus 로고    scopus 로고
    • Efficient minimization method for a generalized total variation functional
    • P. Rodriguez, and B. Wohlberg Efficient minimization method for a generalized total variation functional IEEE Trans. Image Process. 18 2 2009 322 332
    • (2009) IEEE Trans. Image Process. , vol.18 , Issue.2 , pp. 322-332
    • Rodriguez, P.1    Wohlberg, B.2
  • 28
    • 7044231546 scopus 로고    scopus 로고
    • An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
    • I. Daubechies, M. Defrise, and C. De Mol An iterative thresholding algorithm for linear inverse problems with a sparsity constraint Commun. Pure Appl. Math. 57 2004 1413 1457
    • (2004) Commun. Pure Appl. Math. , vol.57 , pp. 1413-1457
    • Daubechies, I.1    Defrise, M.2    De Mol, C.3
  • 29
    • 77955783919 scopus 로고    scopus 로고
    • Fast image recovery using variable splitting and constrained optimization
    • M. Afonso, J. B-Dias, and M. Figueiredo Fast image recovery using variable splitting and constrained optimization IEEE Trans. Image Process. 19 9 2010 2345 2356
    • (2010) IEEE Trans. Image Process. , vol.19 , Issue.9 , pp. 2345-2356
    • Afonso, M.1    B-Dias, J.2    Figueiredo, M.3
  • 30
    • 33847715169 scopus 로고    scopus 로고
    • Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising
    • J. Xu, and S. Osher Iterative regularization and nonlinear inverse scale space applied to wavelet-based denoising IEEE Trans. Image Process. 16 2 2007 534 544
    • (2007) IEEE Trans. Image Process. , vol.16 , Issue.2 , pp. 534-544
    • Xu, J.1    Osher, S.2
  • 31
    • 33646554522 scopus 로고    scopus 로고
    • Nonlinear inverse scale space methods for image restoration
    • M. Burger, S. Osher, J. Xu, and G. Gilboa Nonlinear inverse scale space methods for image restoration Lect. Notes Comput. Sci. 3752 2005 25 36
    • (2005) Lect. Notes Comput. Sci. , vol.3752 , pp. 25-36
    • Burger, M.1    Osher, S.2    Xu, J.3    Gilboa, G.4
  • 33
    • 78149351664 scopus 로고    scopus 로고
    • Alternating direction algorithms for l1 problems in compressive sensing
    • Rice University
    • J. Yang, Y. Zhang, Alternating direction algorithms for l1 problems in compressive sensing, Technical Report, Rice University, 2009.
    • (2009) Technical Report
    • Yang, J.1    Zhang, Y.2
  • 34
    • 85014561619 scopus 로고    scopus 로고
    • A fast iterative shrinkage-thresholding algorithm for linear inverse problems
    • A. Beck, and M. Teboulle A fast iterative shrinkage-thresholding algorithm for linear inverse problems SIAM J. Imaging Sci. 2 1 2009 183 202
    • (2009) SIAM J. Imaging Sci. , vol.2 , Issue.1 , pp. 183-202
    • Beck, A.1    Teboulle, M.2
  • 35
    • 77949403269 scopus 로고    scopus 로고
    • Recursive least squares dictionary learning algorithm
    • K. Skretting, and K. Engan Recursive least squares dictionary learning algorithm IEEE Trans. Signal Process. 58 4 2010 2121 2130
    • (2010) IEEE Trans. Signal Process. , vol.58 , Issue.4 , pp. 2121-2130
    • Skretting, K.1    Engan, K.2
  • 37
    • 78649858822 scopus 로고    scopus 로고
    • Robust kernel regression for restoration and reconstruction of images from sparse noisy data
    • H. Takeda, S. Farsiu, and P. Milanfar Robust kernel regression for restoration and reconstruction of images from sparse noisy data In ICIP. 2006 1257 1260
    • (2006) ICIP , pp. 1257-1260
    • Takeda, H.1    Farsiu, S.2    Milanfar, P.3
  • 38
    • 1942436689 scopus 로고    scopus 로고
    • Image quality assessment: From error visibility to structural similarity
    • Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli Image quality assessment: from error visibility to structural similarity IEEE Trans. Image Process. 13 4 2004 600 612
    • (2004) IEEE Trans. Image Process. , vol.13 , Issue.4 , pp. 600-612
    • Wang, Z.1    Bovik, A.C.2    Sheikh, H.R.3    Simoncelli, E.P.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.