High-Quality Light Field Microscope Imaging Based on Microlens Arrays

被引:2
作者
Gu, Tongkai [1 ,2 ,3 ]
Yan, Sitong [4 ,5 ]
Wang, Lanlan [3 ,6 ]
Chang, Yasheng [2 ,3 ,4 ]
Liu, Hongzhong [3 ,6 ]
机构
[1] Xian Univ Architecture & Technol, Sch Mech & Elect Engn, Xian 710055, Peoples R China
[2] Suzhou City Univ, Suzhou Key Lab Biophoton, Suzhou 215104, Peoples R China
[3] Xi An Jiao Tong Univ, State Key Lab Mfg Syst Engn, Xian 710054, Peoples R China
[4] Suzhou City Univ, Sch Opt & Elect Informat, Suzhou 215104, Peoples R China
[5] Suzhou Univ, Sch Comp Sci & Technol, Suzhou 215031, Peoples R China
[6] Xi Jiaotong Univ, Sch Mech Engn, State Key Lab Mfg Syst Engn, 28 Xianning West Rd, Xian 710049, Peoples R China
关键词
Light fields; Optical microscopy; Light field microscope; microlens arrays; image segmentation; imaging quality;
D O I
10.1109/JMEMS.2023.3349299
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
High-quality optical observation through traditional microscopes faces significant challenges due to their low spatial sampling and the limited ability to respond only to the light intensity characteristics of optoelectronic devices. This limitation results in an inability to measure other critical optical information during imaging, such as phase, angle, polarization, and coherence. In response to these challenges, light field microscope (LFM) as a powerful imaging technique is capable of measuring samples with unprecedented depth and detail. LFM overcomes the limitations of conventional microscope methods by capturing both spatial and angular information of light rays. To further demonstrate these capabilities, the LFM based on microlens arrays is constructed here. These arrays are fabricated using advanced techniques such as laser lithography, microimprinting, and self-assembly technology. Using light field imaging, image segmentation methods, and deep learning fusion, the imaging quality is nearly doubled, significantly enhancing the quality of observations. LFM based on microlens arrays offers great promise for improving the quality of imaging observations in the field of microsope.2023-0167
引用
收藏
页码:296 / 303
页数:8
相关论文
共 28 条
[1]   High Contrast Ultrathin Light-Field Camera Using Inverted Microlens Arrays with Metal-Insulator-Metal Optical Absorber [J].
Bae, Sang-In ;
Kim, Kisoo ;
Jang, Kyung-Won ;
Kim, Hyun-Kyung ;
Jeong, Ki-Hun .
ADVANCED OPTICAL MATERIALS, 2021, 9 (06)
[2]   Wave optics theory and 3-D deconvolution for the light field microscope [J].
Broxton, Michael ;
Grosenick, Logan ;
Yang, Samuel ;
Cohen, Noy ;
Andalman, Aaron ;
Deisseroth, Karl ;
Levoy, Marc .
OPTICS EXPRESS, 2013, 21 (21) :25418-25439
[3]   An Improved BM3D Algorithm Based on Image Depth Feature Map and Structural Similarity Block-Matching [J].
Cao, Jia ;
Qiang, Zhenping ;
Lin, Hong ;
He, Libo ;
Dai, Fei .
SENSORS, 2023, 23 (16)
[4]   A Deep Learning-Based Weld Defect Classification Method Using Radiographic Images With a Cylindrical Projection [J].
Chang, Yasheng ;
Wang, Weiku .
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2021, 70
[5]   In situ 3D nanoprinting of free-form coupling elements for hybrid photonic integration [J].
Dietrich, P. -I. ;
Blaicher, M. ;
Reuter, I. ;
Billah, M. ;
Hoose, T. ;
Hofmann, A. ;
Caer, C. ;
Dangel, R. ;
Offrein, B. ;
Troppenz, U. ;
Moehrle, M. ;
Freude, W. ;
Koos, C. .
NATURE PHOTONICS, 2018, 12 (04) :241-+
[6]   Trilobite-inspired neural nanophotonic light-field camera with extreme depth-of-field [J].
Fan, Qingbin ;
Xu, Weizhu ;
Hu, Xuemei ;
Zhu, Wenqi ;
Yue, Tao ;
Zhang, Cheng ;
Yan, Feng ;
Chen, Lu ;
Lezec, Henri J. ;
Lu, Yanqing ;
Agrawal, Amit ;
Xu, Ting .
NATURE COMMUNICATIONS, 2022, 13 (01)
[7]   Camera Array for Multi-Spectral Imaging [J].
Genser, Nils ;
Seiler, Jurgen ;
Kaup, Andre .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 29 :9234-9249
[8]  
Gissibl T, 2016, NAT PHOTONICS, V10, P554, DOI [10.1038/NPHOTON.2016.121, 10.1038/nphoton.2016.121]
[9]   SOFFLFM: Super-resolution optical fluctuation Fourier light-field microscopy [J].
Huang, Haixin ;
Qiu, Haoyuan ;
Wu, Hanzhe ;
Ji, Yihong ;
Li, Heng ;
Yu, Bin ;
Chen, Danni ;
Qu, Junle ;
Qu, Junle .
JOURNAL OF INNOVATIVE OPTICAL HEALTH SCIENCES, 2023, 16 (03)
[10]   Light field imaging for computer vision: a survey [J].
JIA, Chen ;
SHI, Fan ;
ZHAO, Meng ;
CHEN, Shengyong .
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, 2022, 23 (07) :1077-1097