[1] LI Y B, LI X L, JIANG Y M. Micro-focus X-ray CT and its application in nondestructive testing [J]. Nondestructive Testing, 1999, 21(12): 549-552. (in Chinese)
[2] LI L, CHEN ZH, ZHANG X M. BGA solder joints defect detection based on precision micro-focus X-ray [J].Electronic Design Engineering, 2014, 22(12): 164-166+170. (in Chinese)
[4] WU Z, GAO H, MA G, et al.. A dual adaptive regularization method to remove mixed Gaussian-Poisson noise [C]. Proceedings of 13th Asian Conference on Computer Vision, Springer, Cham, 2016: 206-221.
[6] SPERL J, BEQUE D, CLAUS B, et al.. Computer-assisted scan protocol and reconstruction (CASPAR)—reduction of image noise and patient dose [J]. IEEE Transactions on Medical Imaging, 2010, 29(3): 724-732.
[9] LIAN Q SH, SHI B SH, CHEN SH ZH. Research advances on dictionary learning models, algorithms and applications [J]. Acta Automation Sinica, 2015, 41(2): 240-260. (in Chinese)
[10] WEI D H, MAO J L, LIU Y. An improved complementary matching pursuit algorithm for compressed sensing signal reconstruction [C]. Proceedings of International Conference on Advanced Intelligence and Awareness Internet, 2011: 389-393.
[11] MICHAEL E, MICHAL A. Image denoising via sparse and redundant representations over learned dictionaries [J]. IEEE Transactions on Image Processing, 2006, 15(12): 3736-3745.
[12] CHATTERJEE P, MILANFAR P. Clustering-based denoising with locally learned dictionaries [J]. IEEE Transactions on Image Processing, 2009, 18(7): 1438-1451.
[13] MAIRAL J, BACH F, PONCE J, et al.. Non-local sparse models for image restoration [C]. Proceedings of IEEE International Conference on Computer Vision, 2010, 30(2): 2272-2279.
[14] DONG W, LI X, ZHANG L, et al.. Sparsity-based image denoising via dictionary learning and structural clustering [C]. Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, IEEE Computer Society, 2011: 457-464.
[15] HARMANYZ T, MARCIAR F, WILLETT R M. This is SPIRAL-TAP: sparse Poisson intensity reconstruction algorithms-theory and practice [J]. IEEE Trans Image Process., 2012, 21(3): 1084-1096.
[16] WANG X D. Study on image denoising models based on MAP estimation, variation and PDE [D]. Xian: Xidian University, 2013. (in Chinese)
[17] DONOHOD L. Compress sensing[J]. IEEE Transactions on Information Theory, 2006, 52(4):1289-1306.
[18] PU G L, QIU Y H. Image classification based on global dictionary learning method with sparse representation [J].Journal of Computer Applications, 2015, 35(2):499-501. (in Chinese)
[19] GIRYES R, ELAO M. Sparsity based Poissondenoising with dictionary learning [J]. IEEE Transactions on Image Processing, 2014, 23(12): 5057-5069.
[20] YUAN G L, LU X W. An active set limited memory BFGS algorithm for bound constrained optimization [J].Applied Mathematical Modelling, 2011, 35(7): 3561-3573.
[21] HUANG J G, SUN L SH, YE ZH X. Optimization algorithm with Armijo rule on Riemann manifold [J]. Journal of Shanghai Jiaotong University, 2002, 36(2): 267-271. (in Chinese)