[1] Huang D, Swanson E A, Lin C P et al. Optical coherence tomography[J]. Science, 254, 1178-1181(1991).

[2] Brezinski M E[M]. Optical coherence tomography: principles and applications, 333-394(2005).

[3] Choma M A, Sarunic M V, Yang C H et al. Sensitivity advantage of swept source and Fourier domain optical coherence tomography[J]. Optics Express, 11, 2183-2189(2003). http://europepmc.org/abstract/MED/19466106

[4] Goodman J W[M]. Speckle phenomena in optics: theory and applications, 165-166(2009).

[5] Yao X L, Ji K H, Liu G P et al. Blood flow imaging by optical coherence tomography based on speckle variance and doppler algorithm[J]. Laser & Optoelectronics Progress, 54, 031702(2017).

[6] Popov I, Weatherbee A, Vitkin I A. Statistical properties of dynamic speckles from flowing Brownian scatterers in the vicinity of the image plane in optical coherence tomography[J]. Biomedical Optics Express, 8, 2004(2017). http://www.ncbi.nlm.nih.gov/pubmed/28736652

[7] Yang L, Hong W, Wang C et al. Flow velocity measurement based on speckle in optical coherence tomography[J]. Chinese Journal of Lasers, 39, 0504002(2012).

[8] Liba O, Lew M D, Sorelle E D et al. Erratum: speckle-modulating optical coherence tomography in living mice and humans[J]. Nature Communications, 8, 15845(2017). http://www.nature.com/articles/ncomms16131

[9] Adler D C, Ko T H, Fujimoto J G. Speckle reduction in optical coherence tomography images by use of a spatially adaptive wavelet filter[J]. Optics Letters, 29, 2878-2880(2004). http://www.opticsinfobase.org/ol/abstract.cfm?id=82021

[10] Jian Z P, Yu Z X, Yu L F et al. Speckle attenuation in optical coherence tomography by curvelet shrinkage[J]. Optics Letters, 34, 1516-1518(2009). http://pubmedcentralcanada.ca/pmcc/articles/PMC2860949/

[11] Wang L Z, Meng Z, Yao X S et al. Adaptive speckle reduction in OCT volume data based on block-matching and 3-d filtering[J]. IEEE Photonics Technology Letters, 24, 1802-1804(2012). http://ieeexplore.ieee.org/document/6310105/

[12] Yu H C, Gao J L, Li A T. Probability-based non-local means filter for speckle noise suppression in optical coherence tomography images[J]. Optics Letters, 41, 994-997(2016). http://europepmc.org/abstract/MED/26974099

[13] Moore B C. Principal component analysis in linear systems: controllability, observability, and model reduction[J]. IEEE Transactions on Automatic Control, 26, 17-32(1981). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1102568

[14] Wright J, Ganesh A, Rao S et al. Robust principal component analysis: exact recovery of corrupted low-rank matrices[C]. Advances in Neural Information Processing Systems, 2080-2088(2009).

[15] Candès E J, Recht B. Exact matrix completion via convex optimization[J]. Foundations of Computational Mathematics, 9, 717(2009). http://biomet.oxfordjournals.org/external-ref?access_num=10.1007/s10208-009-9045-5&link_type=DOI

[16] Candès E J, Li X D, Ma Y et al. Robust principal component analysis?[J]. Journal of the ACM, 58, 11(2009).

[17] [17] Lin ZC, Chen MM, MaY, et al. The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices[J]. arXiv Preprint arXiv:1009.5055, 2010.

[18] Huynh-Thu Q, Ghanbari M. Scope of validity of PSNR in image/video quality assessment[J]. Electronics Letters, 44, 800-801(2008). http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4550695

[19] Donoho D L, Johnstone J M. Ideal spatial adaptation by wavelet shrinkage[J]. Biometrika, 81, 425-455(1994). http://biomet.oxfordjournals.org/biomet/article/81/3/425/256924/Ideal-spatial-adaptation-by-wavelet-shrinkage

[20] Welvaert M, Rosseel Y. On the definition of signal-to-noise ratio and contrast-to-noise ratio for fMRI data[J]. Plos One, 8, e77089(2013). http://pubmedcentralcanada.ca/articlerender.cgi?accid=PMC3819355

[21] Anfinsen S N, Doulgeris A P, Eltoft T. Estimation of the equivalent number of looks in polarimetric synthetic aperture radar imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 47, 3795-3809(2009). http://ieeexplore.ieee.org/document/5071293/