Two soft-thresholding based iterative algorithms for image deblurring

Information Sciences

Volumn 271, Issue , 2014, Pages 179-195

  Huang, Jie ^a   Huang, Ting Zhu ^a   Zhao, Xi Le ^a   Xu, Zong Ben ^b   Lv, Xiao Guang ^a  

^a UNIVERSITY OF ELECTRONIC SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Filter; Image deblurring; Iterative algorithms; Regularization; Soft thresholding

Indexed keywords

ALGORITHMS; IMAGE ENHANCEMENT;

FILTER; IMAGE DEBLURRING; ITERATIVE ALGORITHM; REGULARIZATION; SOFT-THRESHOLDING;

ITERATIVE METHODS;

EID: 84898785224     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2014.02.089     Document Type: Article

References (55)

1. D. Alassi, and R. Alhajj Effectiveness of template detection on noise reduction and websites summarization Inform. Sci. 219 2013 41 72
2. J.M. Bardsley, and J.G. Nagy Covariance-preconditioned iterative methods for nonnegatively constrained astronomical imaging SIAM J. Matrix Anal. Appl. 27 2006 1184 1198
3. F.S. Viloche Bazán Fixed-point iterations in determining the Tikhonov regularization parameter Inverse Probl. 24 2008 035001
4. F.S. Viloche Bazán, and L.S. Borges GKB-FP: an algorithm for large-scale discrete ill-posed problems BIT 50 2010 481 507
5. A. Beck, and M. Teboulle A fast iterative shrinkage-thresholding algorithm for linear inverse problems SIAM J. Imag. Sci. 2 2009 183 202
6. G. Bhatnagar, Q.M. Jonathan Wu, and B. Raman Discrete fractional wavelet transform and its application to multiple encryption Inform. Sci. 223 2013 297 316
7. A. Björck Numerical Methods for Least Squares Problems 1996 SIAM Philadelphia
8. A. Björck A bidiagonalization algorithm for solving large and sparse ill-posed systems of linear equations BIT 28 1988 659 670
9. A. Björck, E. Grimme, and P. Van Dooren An implicit shift bidiagonalization algorithm for ill-posed systems of linear equations BIT 34 1994 510 534
10. J. Bolz, I. Farmer, E. Grinspun, and P. Schröder Sparse matrix solvers on the GPU: conjugate gradients and multigrid ACM Trans. Graph. 22 2003 917 924
11. D. Calvetti, B. Lewis, and L. Reichel GMRES-type methods for inconsistent systems Linear Algebra Appl. 316 2000 157 169
12. D. Calvetti, and L. Reichel Tikhonov regularization of large linear problems BIT 43 2003 263 283
13. D.Q. Chen, and L.Z. Cheng Deconvolving Poissonian images by a novel hybrid variational model J. Visual Commun. Image Rep. 22 2011 643 652
14. J. Chung, J.G. Nagy, and D.P. O'Leary A weighted-GCV method for Lanczos-hybrid regularization Electron. Trans. Numer. Anal. 28 2008 149 167
15. 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
16. M. Donatelli, C. Estatico, A. Martinelli, and S. Serra-Capizzano Improved image deblurring with anti-reflective boundary conditions and re-blurring Inverse Probl. 22 2006 2035 2053
17. M. Donatelli, and S. Serra-Capizzano Anti-reflective boundary conditions and re-blurring Inverse Probl. 21 2005 169 182
18. H.W. Engl, M. Hanke, and A. Neubauer Regularization of Inverse Problems 2000 Kluwer Academic Publishers Dordrecht
19. X.B. Gao, Q. Wang, X.L. Li, D.C. Tao, and K.B. Zhang Zernike-moment-based image super resolution IEEE Trans. Image Process. 20 2011 2738 2747
20. X.B. Gao, K.B. Zhang, D.C. Tao, and X.L. Li Joint learning for single-image super-resolution via a coupled constraint IEEE Trans. Image Process. 21 2012 469 480
21. G.H. Golub, M. Heath, and G. Wahba Generalized cross-validation as a method for choosing a good ridge parameter Technometrics 21 1979 215 222
22. N.Y. Guan, D.C. Tao, Z.G. Luo, and B. Yuan NeNMF: an optimal gradient method for nonnegative matrix factorization IEEE Trans. Signal Process. 60 2012 2882 2898
23. Q. Guo, S.Y. Chen, H. Leung, and S.T. Liu Covariance intersection based image fusion technique with application to pansharpening in remote sensing Inform. Sci. 180 2010 3434 3443
24. X.H. Han, and X.M. Chang An intelligent noise reduction method for chaotic signals based on genetic algorithms and lifting wavelet transforms Inform. Sci. 218 2013 103 118
25. M. Hanke Conjugate Gradient Type Methods for Ill-Posed Problems 1995 Longman Scientific & Technical Harlow, UK
26. M. Hanke On Lanczos based methods for the regularization of discrete ill-posed problems BIT 41 2001 1008 1018
27. M. Hanke, and P.C. Hansen Regularization methods for large-scale problems Surveys Math. Indust. 3 1993 253 315
28. P.C. Hansen Rank-Deficient and Discrete Ill-Posed Problems: Numerical Aspects of Linear Inversion 1998 SIAM Philadelphia
29. P.C. Hansen Regularization tools version 4.0 for Matlab 7.3 Numer. Algor. 46 2007 189 194
30. P.C. Hansen, J.G. Nagy, and D.P. O'Leary Deblurring Images: Matrices, Spectra, and Filtering 2006 SIAM Philadelphia
31. M.R. Hestenes, and E. Stiefel Methods of conjugate gradients for solving linear systems J. Res. Nat. Bur. Standards 49 1952 409 436
32. G. Jeon, M. Anisetti, V. Bellandi, E. Damiani, and J. Jeong Designing of a type-2 fuzzy logic filter for improving edge-preserving restoration of interlaced-to-progressive conversion Inform. Sci. 179 2009 2194 2207
33. M.F. Jiang, L. Xia, G.F. Shou, F. Liu, and S. Crozier Two hybrid regularization frameworks for solving the electrocardiography inverse problem Phys. Med. Biol. 53 2008 5151 5164
34. L. Kaufman Maximum likelihood, least squares, and penalized least squares for PET IEEE Trans. Med. Imag. 12 1993 200 214
35. M.E. Kilmer, P.C. Hansen, and M.I. Espanol A projected-based approach to general-form Tikhonov regularization SIAM J. Sci. Comput. 29 2007 315 330
36. M.E. Kilmer, and D.P. O'Leary Choosing regularization parameters in iterative methods for ill-posed problems SIAM J. Matrix Anal. Appl. 22 2001 1204 1221
37. H. Kim, and H. Park Nonnegative matrix factorization based on alternating non-negativity constrained least squares and active set method SIAM J. Matrix Anal. Appl. 30 2008 713 730
38. J.S. Lim Two-Dimensional Signal and Image Processing 1990 Prentice-Hall New Jersey
39. T.C. Lin, and C.M. Lin Wavelet-based copyright-protection scheme for digital images based on local features Inform. Sci. 179 2009 3349 3358
40. X.-G. Lv, T.-Z. Huang, Z. Xu, and X.-L. Zhao Kronecker product approximations for image restoration with whole-sample symmetric boundary conditions Inform. Sci. 186 2012 150 163
41. V.A. Morozov Regularization Methods for Solving Incorrectly Posed Problems 1984 Springer-Verlag New York
42. J.G. Nagy, and K.M. Palmer Steepest descent, CG, and iterative regularization of ill-posed problems BIT 43 2003 1003 1017
43. J.G. Nagy, K.M. Palmer, and L. Perrone Iterative methods for image deblurring: a Matlab object-oriented approach Numer. Algor. 36 2004 73 93
44. J.G. Nagy, Z. Strakos, Enforcing nonnegativity in image reconstruction algorithms, in: David C. Wilson et al. (Eds.), Mathematical Modeling, Estimation, and Imaging, vol. 4121, 2000, pp. 182-190.
45. D.P. O'Leary, and J.A. Simmons A bidiagonalization-regularization procedure for large scale discretizations of ill-posed problems SIAM J. Sci. Stat. Comput. 2 1981 474 489
46. W.K. Pratt Digital Image Processing fourth ed. 2007 John Wiley & Sons Hoboken
47. M.C. Roggemann, and B. Welsh Imaging Through Turbulence 1996 CRC Press Boca Raton, Florida
48. D.D. Sha, and J.P. Sutton Towards automated enhancement, segmentation and classification of digital brain images using networks of networks Inform. Sci. 138 2001 45 77
49. M.L. Song, D.C. Tao, C. Chen, J.J. Bu, J.B. Luo, and C.Q. Zhang Probabilistic exposure fusion IEEE Trans. Image Process. 21 2012 341 357
50. M.L. Song, D.C. Tao, C. Chen, X.L. Li, and C.W. Chen Color to gray: visual cue preservation IEEE Trans. Pattern Anal. Mach. Intell. 32 2010 1537 1552
51. J.G. Sun, C. Fyfe, and M. Crowe Extending Sammon mapping with Bregman divergences Inform. Sci. 187 2012 72 92
52. A.N. Tikhonov Solution of incorrectly formulated problems and the regularization method Soviet Math. Dokl. 4 1963 1035 1038
53. J.W. Tukey Exploratory Data Analysis 1977 Addison-Wesley Reading, Massachusetts
54. C.R. Vogel Computational Methods for Inverse Problems 2002 SIAM Philadelphia
55. C.Y. Wee, and R. Paramesran Measure of image sharpness using eigenvalues Inform. Sci. 177 2007 2533 2552