[1] [1] WU Haibing, ZHANG Liang, GU Guohua, et al. Color image enhancement based on LLL tricolor image denoising and fusion ［J］. Journal of Applied Optics , 2018，39 (1): 57-63.

[2] [2] WANG Min, ZHOU Lei, ZHOU Shudao, et al. Image SVD denoising based on PSNR and wavelet directional feature ［J］. Journal of Applied Optics, 2013, 34 (1): 85-89.

[3] [3] BIJALWAN A, GOYAL A, SETHI N. Wavelet transform based image denoise using threshold approaches［J］. International Journal of Engineering & Advanced Technology, 2012(5):218-221.

[4] [4] AHARON M, ELAD M, BRUCKSTEIN A. The K-SVD: an algorithm for designing overcomplete dictionaries for sparse representation［J］. IEEE Transactions on Signal Processing, 2006, 54(11):4311-4322.

[5] [5] DONG W, ZHANG L, SHI G, et al. Nonlocally centralized sparse representation for image restoration［J］. IEEE Transactions on Image Processing A Publication of the IEEE Signal Processing Society, 2013, 22(4):1620.

[6] [6] JIAO Lijuan, WANG Wenjian, ZHAO Qingshan, et al. Nearest neighbor local OMP sparse representation for image denoising ［J］. Journal of Image and Graphics, 2017, 22 (11): 1486-1492.

[7] [7] DABOV K , FOI A , KATKOVNIK V , et al. Image denoising by sparse 3-D transform-domain collaborative filtering［J］. IEEE Transactions on Image Processing, 2007, 16(8):2080-2095.

[8] [8] BANSAL M, DEVI M, JAIN N, et al. A proposed approach for biomedical image denoising using PCA_NLM［J］. International Journal of Bio-Science & Bio-Technology, 2014, 6(6):13-20.

[9] [9] HAN Zhen, WANG Hongbin, YU Zhengtao, et al. Bilateral non-local mean filter image denoising algorithm ［J］. Transducer and Microsystem Technologies, 2016, 35 (6): 124-127.

[10] [10] HARMELING S, SCHULER C J, BURGER H C. Image denoising: Can plain neural networks compete with BM3D［C］//Providence,RI,USA：IEEE Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 2012:2392-2399.

[11] [11] PAREKH A, SELESNICK I W. Convex denoising using non-convex tight frame regularization［J］. IEEE Signal Processing Letters, 2015, 22(10):1786-1790.

[12] [12] ZORAN D, WEISS Y. From learning models of natural image patches to whole image restoration［J］. 2011, 6669(5):479-486.

[13] [13] GAO Kaijun, SUN Shaoyuan, YAO Guangshun, et al. Semantic segmentation of night vision images based on depth learning ［J］. Journal of Applied Optics, 2017, 38 (3): 421-428.

[14] [14] MARTIN D R, FOWLKES C C, MALIK J. Learning to detect natural image boundaries using local brightness, color, and texture cues［J］.IEEE/Transactions on Pattern Analysis and Machine Intelligence,2004,26(5):530-549.

[15] [15] BEVILACQUA M, ROUMY A, GUILLEMOT C, et al. Single-image super-resolution via linear mapping of interpolated self-examples［J］. IEEE Transactions on Image Processing, 2014, 23(12):5334-47.

[16] [16] ZHANG K, GAO X, TAO D, et al. Single image super-resolution with non-local means and steering kernel regression［J］. IEEE Transactions on Image Processing, 2012, 21(11):4544-4556.