[1] RhodesH, AgranovG, HongC, et al. CMOS imager technology shrinks and image performance[C]//2004 IEEE Workshop on Microelectronics and Electron Devices, April 16-16, 2004, Boise, ID, USA. New York: IEEE, 2004: 7- 18.

[2] Foi A, Trimeche M, Katkovnik V, et al. Practical Poissonian-Gaussian noise modeling and fitting for single-image raw-data[J]. IEEE Transactions on Image Processing, 2008, 17(10): 1737-1754.

[3] 陈曦. 基于深度卷积神经网络的图像去噪[D]. 合肥: 合肥工业大学, 2019.

    ChenX. Image denoising based on deep convolutional neural networks[D]. Hefei: Hefei University of Technology, 2019.

[4] Zhang B Y, Allebach J P. Adaptive bilateral filter for sharpness enhancement and noise removal[J]. IEEE Transactions on Image Processing, 2008, 17(5): 664-678.

[5] Weiss B. Fast median and bilateral filtering[J]. ACM Transactions on Graphics, 2006, 25(3): 519-526.

[6] Buades A, Coll B, Morel J M. A review of image denoising algorithms, with a new one[J]. Multiscale Modeling & Simulation, 2005, 4(2): 490-530.

[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] Burger HC, Schuler CJ, Harmeling S. Image denoising with multi-layer perceptrons, part 1: comparison with existing algorithms and withbounds[EB/OL]. ( 2012-11-09)[2020-04-01]. org/abs/1211. 1544. https://arxiv.

[9] LongJ, ShelhamerE, DarrellT. Fully convolutional networks for semantic segmentation[C]//2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 2015: 3431- 3440.

[10] Zhang K, Zuo W M, Chen Y J, et al. Beyond a Gaussian denoiser: residual learning of deep CNN for image denoising[J]. IEEE Transactions on Image Processing, 2017, 26(7): 3142-3155.

[11] GuoS, Yan ZF, ZhangK, et al. Toward convolutional blind denoising of real photographs[C]//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA. New York: IEEE, 2019: 1712- 1722.

[12] Anaya J, Barbu A. RENOIR - A dataset for real low-light image noise reduction[J]. Journal of Visual Communication and Image Representation, 2018, 51: 144-154.

[13] Grossberg M D, Nayar S K. Modeling the space of camera response functions[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2004, 26(10): 1272-1282.

[14] Malvar HS, He LW, CutlerR. High-quality linear interpolation for demosaicing of Bayer-patterned color images[C]//2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, May 17-21, 2004, Montreal, Que., Canada. New York: IEEE, 2004: 8038960.

[15] Zhou ZW, Rahman Siddiquee M M, Tajbakhsh N, et al. UNet++: a nested U-Net architecture for medical image segmentation[M] //Stoyanov D, Taylor Z, Carneiro G, et al. Deep learning in medical image analysis and multimodal learning for clinical decision support. Lecture notes in computer science. Cham: Springer, 2018, 11045: 3- 11.

[16] XuJ, LiH, Liang ZT, et al. ( 2018-04-07)[2020-04-01]. org/abs/1804. 02603. https://arxiv.

[17] 佟雨兵, 张其善, 祁云平. 基于PSNR与SSIM联合的图像质量评价模型[J]. 中国图象图形学报, 2006, 11(12): 1758-1763.

    Tong Y B, Zhang Q S, Qi Y P. Image quality assessing by combining PSNR with SSIM[J]. Journal of Image and Graphics, 2006, 11(12): 1758-1763.