[1] D DANNHAUSER, D ROSSI, P MEMMOLO. Label-free analysis of mononuclear human blood cells in microfluidic flow by coherent imaging tools. Journal of Biophotonics, 10, 683-689(2016).

[2] T H NGUYEN, M E KANDEK, M RUBESSA. Gradient light interference microscopy for 3D imaging of unlabeled specimens. Nature Communications, 8, 210(2017).

[3] F M MARIA, M ANTHONNY, G W ANETTE. Digital holographic microscopy for non-invasive monitoring of cell cycle arrest in L929 cells. PLoS ONE, 9, e106546(2014).

[4] P MARQUET, C DEPEURSINGE, P J MAGISTRETTI. Exploring neural cell dynamics with digital holographic microscopy. Annual Review of Biomedical Engineering, 15, 407-431(2013).

[5] T TAHARA, R YONESAKA, S YAMAMOTO. High-speed three-dimensional microscope for dynamically moving biological objects based on parallel phase-shifting digital holographic microscopy. IEEE Journal of Selected Topics in Quantum Electronics, 18, 1387-1393(2012).

[6] Wen-hui ZHANG, Liang-cai CAO, Guo-fan JIN. Review on high resolution and large field of view digital holography. Infrared and Laser Engineering, 48, 104-120(2019).

[7] Peng GAO, Kai WEN, Xue-ying SUN. Review of resolution enhancement technologies in quantitative phase microscopy. Infrared and Laser Engineering, 48, 91-103(2019).

[8] Peng GAO, Bao-li YAO, Jun-wei MIN. Autofocusing of digital holographic microscopy based on off-axis illuminations. Optics Letters, 37, 3630-3632(2012).

[9] S CHOWDHURY, J IZATT. Structured illumination quantitative phase microscopy for enhanced resolution amplitude and phaseimaging. Biomedical Optics Express, 4, 1795-1805(2013).

[10] Y K PARK, , Z YAQOOB. Speckle-field digital holographic microscopy. Optics Express, 17, 12285-12292(2009).

[11] X J LAI, C J CHENG, Y C LIN. Angular-polarization multiplexing with spatial light modulators for resolution enhancement in digital holographic microscopy. Journal of Optics, 19, 055607(2017).

[12] V I GUZHOV, S P ILINYKH, I O MARCHENKO. Method of increasing the spatial resolution in digital holographic microscopy. Optoelectronics, Instrumentation and Data Processing, 54, 301-306(2018).

[13] Ming-jun WANG, Shao-dong FENG, Ji-gang WU. Multilayer pixel super-resolution lensless in-line holographic microscope with random sample movement. Scientific Reports, 7, 12791(2017).

[14] Jia-lin ZHANG, Jia-song SUN, Qian CHEN. Adaptive pixel-super-resolved lensfree in-line digital holography for wide-field on-chip microscopy. Scientific Reports, 7, 11777(2017).

[15] Jun SONG, S C LEON, H IM. Sparsity-based pixel super resolution for lens-free digital in-line holography. Scientific Reports, 6, 24681(2016).

[16] Y RIVENSON, Yi-chen WU, Hong-da WANG. Sparsity-based multi-height phase recovery in holographic microscopy. Scientific Reports, 6, 37862(2016).

[17] C FOURNIER, F JOLIVET, L DENIS. Pixel super-resolution in digital holography by regularized reconstruction. Applied Optics, 56, 69-77(2017).

[18] Chao DONG, CC LOY, Kai-ming HE. Image super-resolution using deep convolutional networks. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38, 295-307(2014).

[19] [19] CHRISTIAN L, LUCAS T, FERENC H, et al. Photorealistic single image superresolution using a generative adversarial wk[C]. 2017 IEEE Conference on Computer Vision Pattern Recognition, 2017: 105114.

[20] [20] KAREN S, REW Z. Very deep convolutional wks f largescale image recognition[J]. arXiv: 1409.1556[cs.CV].

[21] [21] LIU Tairan, KEVIN D H, RIVENSON Y, et al. Deep learningbased superresolution in coherent imaging systems[J]. arXiv: 1810.06611[cs.CV].

[22] [22] OLAF R, PHILIPP F, THOMAS B. U: Convolutional wks f biomedical image segmentation[J]. arXiv: 1505.04597[cs.CV].

[23] [23] HE Kaiming, ZHANG Xiangyu, REN Shaoqing, et al. Deep residual learning f image recognition[J]. arXiv: 1512.03385[cs.CV].

[24] [24] CHEN Chao, QI Feng. Single image superresolution using deep CNN with dense skip connections inceptionRes[C]. ITME 2018: IEEE 9th International Conference on Infmation Technology in Medicine Education, 2018, 1: 9991003.

[25] [25] CHRISTIAN S, SERGEY I, VINCENT V. Inceptionv4, inceptionRes the impact of residual connections on learning[J]. arXiv: 1602.07261[cs.CV].

[26] [26] SZEGEDY C, LIU Wei, JIA Yangqing, et al. Going deeper with convolutions[J]. arXiv: 1409.4842[cs.CV].

[27] [27] HU Jie, SHEN Li, SUN Gang. Squeezeexcitation wks[J]. arXiv: 1709.01507[cs.CV].

[28] [28] Categies[EBOL].[20191230]. http:image.gchallengesLSVRC.