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References
ОглавлениеAharon M et al 2006 K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation IEEE Trans. Signal Process. 54 4311
Bell A J and Sejnowski T J 1997 The ‘independent components’ of natural scenes are edge filters Vis. Res. 37 3327–38
Chambolle A 2004 An algorithm for total variation minimization and applications J. Math. Imaging Vis. 20 89–97
Chambolle A and Lions P-L 1997 Image recovery via total variation minimization and related problems Numer. Math. 76 167–88
Dandes E 2006 Near-optimal signal recovery from random projections: universal encoding strategies IEEE Trans. Inform. Theory 52 5406–25
Donoho D L, Tsaig Y, Drori I and Starck J 2012 Sparse solution of underdetermined systems of linear equations by stagewise orthogonal matching pursuit IEEE Trans. Inform. Theory 58 1094–121
Elad M 2010 Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing (Berlin: Springer)
Elbakri I A and Fessler J A 2002 Statistical image reconstruction for polyenergetic x-ray computed tomography IEEE Trans. Med. Imaging 21 89–99
Hastie T, Tibshirani R and Friedman J 2009 The Elements of Statistical Learning: Data Mining Inference and Prediction vol 1 (New York: Springer)
Mairal J, Bach F, Ponce J and Sapiro G 2009 Online dictionary learning for sparse coding Proc. of the 26th Annual Int. Conf. on Machine Learning (New York: ACM) 689–96
Mallat S G and Zhang Z 1993 Matching pursuits with time-frequency dictionaries IEEE Trans. Signal Process. 41 3397–415
Mou X, Wu J, Bai T, Xu Q, Yu H and Wang G 2014 Dictionary learning based low-dose x-ray CT reconstruction using a balancing principle Proc. SPIE 9212 921207
Needell D and Tropp J A 2009 COSAMP: Iterative signal recovery from incomplete and inaccurate samples Appl. Comput. Harmon. Anal. 26 301–21
Needell D and Vershynin R 2010 Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit IEEE J. Sel. Topics Signal Process. 4 310–316
Olshausen B A and Field D J 1996 Emergence of simple-cell receptive field properties by learning a sparse code for natural images Nature 381 607–9
Pati Y C, Rezaiifar R and Krishnaprasad P S 1993 Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition Proc. of 27th Asilomar Conf. on Signals Systems and Computers (Piscataway, NJ: IEEE) 40–4
Sahoo S K and Makur A 2013 Dictionary training for sparse representation as generalization of K-means clustering IEEE Sign. Process Lett. 20 587–90
Rubinstein R, Zibulevsky M and Elad M 2008 Efficient implementation of the K-SVD algorithm using batch orthogonal matching pursuit Technical report CS Technion http://www.cs.technion.ac.il/˜ronrubin/Publications/KSVD-OMP-v2.pdf
Xu Q, Yu H, Mou X, Zhang L, Hsieh J and Wang G 2012 Low-dose x-ray CT reconstruction via dictionary learning IEEE Trans. Med. Imaging 31 1682–97