[1] [1] XU W J, TANG Ch.Two parabolic-hyperbolic oriented partial diffe-rential equations for denoising in electronic speckle pattern interferometry fringes［J］.Applied Optics, 2015, 54(15): 4720-4726.

[2] [2] LI B Y,TANG Ch. General filtering method for electronic speckle pa-ttern interferometry fringe images with various densities based on variational image decomposition［J］.Applied Optics, 2017, 56(16): 4843-4853.

[3] [3] ZHOU Q L, TANG Ch, WANG L L. A daptive oriented PDEs filter-ing methods based on new controlling speedfunction for discontinuous optical fringe patterns［J］.Optics and Lasers in Engineering, 2018, 100: 111-117.

[4] [4] RONG W X, QIAN X F, LIU B, et al.Algorithm of in-plane displacement measured by speckle photography based on phase of Fourier transform［J］.Laser Technology,2017,41(4): 473-478(in Chin-ese).

[5] [5] WANG M, WEN Y W, CHEN Zh B.Semi-smooth Newton method for total variation noise removal［J］.Laser Technology,2017,41(2): 289-295(in Chinese).

[6] [6] GU G Q, WANG K F, YAN X J.Electron speckle interference image processing based on homomorphic filtering［J］.Laser Technology, 2010, 34(6): 750-752(in Chinese).

[7] [7] LANG Ch P, YANG R H. High quality infrared video image restoration algorithm based on the improved ridgelet transform［J］.Laser Technology, 2015, 39(2): 247-251(in Chinese).

[8] [8] LI X, ZHANG W M.Study on speckle noise filter in the ESPI image based on curvelet transform［J］. Laser & Infrared, 2011, 41(9): 1045-1048(in Chinese).

[9] [9] REN H W. Key techniques of phase retrieval for ESPI and experimental research on dynamic thermal deformation of circuit system［D］.Tianjin: Tianjin University, 2013: 47-51(in Chinese).

[10] [10] XU W J, TANG Ch. Combination of oriented partial differential equation and shearlet transform for denoising in electronic speckle pattern interferometry fringe patterns［J］.Applied Optics, 2017, 56(10): 2843-2850.

[11] [11] WU Y Q, YIN J, CAO Zh Q. Fusion of infrared thermal wave image based on nonsubsampledshearlet transform and weighted nonnegative matrix factorization［J］.Acta Photonica Sinica, 2014, 43(10): 1010001(in Chinese).

[12] [12] LIU L, JIA Z, YANG J. A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking［J］. Medical Device & Sensors, 2015, 25(3): 199-205.

[13] [13] LI C J, YANG H X, CAI Y Y, et al.Image denoising algorithm based on nonsubsampled contourlet transform and bilateral filtering［C］//2015 International Conference on Computer Information Systems and Industrial Applications.Bangkok:Atlantis Press,2015:666-669.

[14] [14] TIAN X, JIAO L, GUO K. An affinity-based algorithm in nonsubsampled contourlet transform domain: application to synthetic aperture radar image denoising［J］.Journal of Signal Processing Systems, 2016, 83(3): 373-388.

[15] [15] CHEN P, ZHAN Y, JIA Z, et al.Remote sensing image change detection based on NSCT-HMT model and its application［J］. Sensors, 2017, 17(6):1-15.

[16] [16] GUO H, LI X J.Non-subsampled contourlet transform algorithm to promote detail information capturing ability［J］.Journal of Image and Graphics, 2012, 17(8): 920-922(in Chinese).

[17] [17] STARCK J L, CANDES E J, DONOHO D L, et al. The curvelet transform for image denoising［J］. IEEE Transactions on Image Processing, 2002, 11(6): 670-684.

[18] [18] LIU Y, LI Y B, LI A. NSCT underwater image threshold denoising algorithm based on double filtering［J］.Journal of Harbin Engineering University, 2013, 34(2): 252-255(in Chinese).

[19] [19] FROMENT J. Parameter-free fast pixelwise non-local means denoising［J］. Image Processing on Line, 2014(4): 300-326.

[20] [20] PERONA P, MALIK J. Scale-space and edge detection using anisotropic diffusion［J］.IEEE Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-639.

[21] [21] ALVAREZ L, LIONS P L, MOREL J M.Image selective smoothing and edge detection by nonlinear diffusion［J］.Siam Journal on Numerical Analysis, 1992, 29(3): 845-866.

[22] [22] BUADES A, COLL B, MOREL J M. A non-local algorithm for image denoising［C］//2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.San Diego,USA: IEEE Xplore, 2005,2(7): 60-65.