[1] 王雪， 刘虹遥， 路鑫超， 等. 无透镜全息显微细胞成像［J］. 光学 精密工程， 2020， 28（8）： 1644-1650. doi: 10.3788/OPE.20202808.1644WANGX， LIUH Y， LUX C， et al. Cell imaging by holographic lens-free microscopy［J］. Opt. Precision Eng.， 2020， 28（8）： 1644-1650.（in Chinese）. doi: 10.3788/OPE.20202808.1644
[2] L F ZHOU, H W YU, Y LAN et al. CANet： an unsupervised deep convolutional neural network for efficient cluster-analysis-based multibaseline InSAR phase unwrapping. IEEE Transactions on Geoscience and Remote Sensing, 60, 5212315(2022).
[3] F G HAO, C TANG, M XU et al. Batch denoising of ESPI fringe patterns based on convolutional neural network. Applied Optics, 58, 3338-3346(2019).
[4] 李洋洋， 吴思进， 李伟仙， 等. 双功能数字散斑干涉位移及空间梯度同时测量［J］. 光子学报， 2020， 49（6）： 0612002. doi: 10.3788/gzxb20204906.0612002LIY Y， WUS J， LIW X， et al. Simultaneous measurement of displacement and slope with dual-function digital speckle pattern interferometry［J］. Acta Photonica Sinica， 2020， 49（6）： 0612002.（in Chinese）. doi: 10.3788/gzxb20204906.0612002
[5] Y LIU, Z WANG, J H HUANG. Recent progress on aberration compensation and coherent noise suppression in digital holography. Applied Sciences, 8, 444(2018).
[6] Y LIU, P H BU, M X JIAO et al. Dynamic speckle illumination digital holographic microscopy by doubly scattered system. Photonics, 8, 276(2021).
[7] A GOREVOY, O POLSCHIKOVA, A MACHIKHIN et al. Multi-wavelength off-axis digital holographic microscopy with broadly tunable low-coherent sources： theory， performance and limitations. Journal of Optics, 24, 115701(2022).
[8] 刘芸， 刘雨萌， 卜佩华， 等. 旋转双散射片散斑抑制方法［J］. 光学学报， 2023， 43（4）： 3788/AOS221528. doi: 10.3788/AOS221528LIUY， LIUY M， BUP H， et al. Speckle suppression method based on rotating double diffusers［J］. Acta Optica Sinica， 2023， 43（4）： 3788/AOS221528.（in Chinese）. doi: 10.3788/AOS221528
[9] 王阳， 张美玲， 王宇， 等. 部分相干光照明的数字全息显微技术及应用［J］. 激光与光电子学进展， 2021， 58（18）： 1811005. doi: 10.3788/LOP202158.1811005WANGY， ZHANGM L， WANGY， et al. Partially coherent illumination-based digital holographic microscopy and its applications［J］. Laser & Optoelectronics Progress， 2021， 58（18）： 1811005.（in Chinese）. doi: 10.3788/LOP202158.1811005
[10] Y LIU, Z WANG, J H HUANG et al. Coherent noise reduction of reconstruction of digital holographic microscopy using a laterally shifting hologram aperture. Optical Engineering, 55, 121725(2016).
[11] 赵夫群， 周明全. 层次化点云去噪算法［J］. 光学 精密工程， 2020， 28（7）： 1618-1625. doi: 10.37188/OPE.20202807.1618ZHAOF Q， ZHOUM Q. Hierarchical point cloud denoising algorithm［J］. Opt. Precision Eng.， 2020， 28（7）： 1618-1625.（in Chinese）. doi: 10.37188/OPE.20202807.1618
[12] H A AEBISCHER, S WALDNER. A simple and effective method for filtering speckle-interferometric phase fringe patterns. Optics Communications, 162, 205-210(1999).
[13] A UZAN, Y RIVENSON, A STERN. Speckle denoising in digital holography by nonlocal means filtering. Applied Optics, 52, A195-A200(2013).
[14] Y ROMANO, M ELAD. Improving K-SVD denoising by post-processing its method-noise, 435-439(2013).
[15] K T YAN, L CHANG, M ANDRIANAKIS et al. Deep learning-based wrapped phase denoising method for application in digital holographic speckle pattern interferometry. Applied Sciences, 10, 4044(2020).
[16] J M LI, C TANG, M XU et al. DBDNet for denoising in ESPI wrapped phase patterns with high density and high speckle noise. Applied Optics, 60, 10070-10079(2021).
[17] J GURROLA-RAMOS, O DALMAU, T ALARCÓN. U-Net based neural network for fringe pattern denoising. Optics and Lasers in Engineering, 149, 106829(2022).
[18] 周文静， 邹帅， 何登科， 等. 频谱卷积神经网络实现全息图散斑降噪［J］. 光学学报， 2020， 40（5）： 0509001. doi: 10.3788/aos202040.0509001ZHOUW J， ZOUS， HED K， et al. Speckle noise reduction of holograms based on spectral convolutional neural network［J］. Acta Optica Sinica， 2020， 40（5）： 0509001.（in Chinese）. doi: 10.3788/aos202040.0509001
[19] K ZHANG, W M ZUO, L ZHANG. FFDNet： toward a Fast and Flexible Solution for CNN based Image Denoising. IEEE Transactions on Image Processing： a Publication of the IEEE Signal Processing Society, 4608-4622(2018).
[20] Z ZHU, M D XU, S BAI et al. Asymmetric non-local neural networks for semantic segmentation, 593-602(2019).
[21] W LU, Y SHI, J H YUE et al. Complex-valued speckle effect and its suppression for high quality of phase unwrapping reconstruction in coherent digital holographic microscopy. Optics Communications, 472, 125837(2020).
[22] L Y MA, L MOISAN, J YU et al. A dictionary learning approach for Poisson image deblurring. IEEE Transactions on Medical Imaging, 32, 1277-1289(2013).
[23] L RUDIN, P L LIONS, S OSHER.
[24] X L WANG, R GIRSHICK, A GUPTA et al. Non-local neural networks, 7794-7803(2018).
[25] K M HE, X Y ZHANG, S Q REN et al. Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 1904-1916(2015).
[26] W Z SHI, J CABALLERO, F HUSZÁR et al. Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network, 1874-1883(2016).
[27] S KAREB, Z ANDREW. Very deep convolutional networks for large-scale image recognition, 1-14(2015).
[28] K Q WANG, Y LI, K M QIAN et al. One-step robust deep learning phase unwrapping. Optics Express, 27, 15100-15115(2019).
[29] 刘言， 陈刚， 喻春雨， 等. 基于Res2-Unet多阶段监督的图像降噪［J］. 光学 精密工程， 2023， 31（6）： 920-935. doi: 10.37188/ope.20233106.0920LIUY， CHENG， YUC Y， et al. Deep learning image denoising based on multi-stage supervised with Res2-Unet［J］. Opt. Precision Eng.， 2023， 31（6）： 920-935.（in Chinese）. doi: 10.37188/ope.20233106.0920
[30] 陈朋， 徐泽楠， 赵冬冬， 等. ANLResNet网络的前视声呐图像散斑去噪方法［J］. 小型微型计算机系统， 2022， 43（2）： 355-361.CHENP， XUZ N， ZHAOD D， et al. Despeckling for forward looking sonar image based on ANLResNet［J］. Journal of Chinese Computer Systems， 2022， 43（2）： 355-361.（in Chinese）
[31] K ZHANG, W M ZUO, Y J CHEN et al. Beyond a Gaussian denoiser： residual learning of deep CNN for image denoising. IEEE Transactions on Image Processing： a Publication of the IEEE Signal Processing Society, 26, 3142-3155(2017).
[32] 王华英， 刘佐强， 廖薇， 等. 基于最小范数的四种相位解包裹算法比较［J］. 中国激光， 2014， 41（2）： 0209016. doi: 10.3788/cjl201441.0209016WANGH Y， LIUZ Q， LIAOW， et al. Comparison of four phases unwrapping algorithm based on method of minimum norm［J］. Chinese Journal of Lasers， 2014， 41（2）： 0209016.（in Chinese）. doi: 10.3788/cjl201441.0209016
