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Ye M, Gao Z, Zhu W, Liu K, Wang Z, Zhang X. LC-based lightfield camera prototype for rapidly creating target images optimized by finely adjusting several key coefficients and a LC-guided refocusing-rendering. OPTICS EXPRESS 2024; 32:7220-7242. [PMID: 38439409 DOI: 10.1364/oe.517843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 02/02/2024] [Indexed: 03/06/2024]
Abstract
A lightfield camera prototype is constructed by directly coupling a liquid-crystal (LC) microlens array with an arrayed photosensitive sensor for performing a LC-guided refocusing-rendering imaging attached by computing disparity map and extracting featured contours of targets. The proposed camera prototype presents a capability of efficiently selecting the imaging clarity value of the electronic targets interested. Two coefficients of the calibration coefficient k and the rendering coefficient C are defined for quantitively adjusting LC-guided refocusing-rendering operations about the images acquired. A parameter Dp is also introduced for exactly expressing the local disparity of the electronic patterns selected. A parallel computing architecture based on common GPU through the OpenCL platform is adopted for improving the real-time performance of the imaging algorithms proposed, which can effectively be used to extract the pixel-leveled disparity and the featured target contours. In the proposed lightfield imaging strategy, the focusing plane can be easily selected and/or further adjusted by loading and/or varying the signal voltage applied over the LC microlenses for realizing a rapid or even intelligent autofocusing. The research lays a solid foundation for continuously developing or upgrading current lightfield imaging approaches.
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Chen M, Shao Q, He W, Wei D, Hu C, Shi J, Liu K, Wang H, Xie C, Zhang X. Electrically Controlled Liquid Crystal Microlens Array Based on Single-Crystal Graphene Coupling Alignment for Plenoptic Imaging. MICROMACHINES 2020; 11:E1039. [PMID: 33256175 PMCID: PMC7760086 DOI: 10.3390/mi11121039] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 11/19/2020] [Accepted: 11/25/2020] [Indexed: 11/21/2022]
Abstract
As a unique electric-optics material, liquid crystals (LCs) have been used in various light-control applications. In LC-based light-control devices, the structural alignment of LC molecules is of great significance. Generally, additional alignment layers are required for LC lens and microlens, such as rubbed polyimide (PI) layers or photoalignment layers. In this paper, an electrically controlled liquid crystal microlens array (EC-LCMLA) based on single-crystal graphene (SCG) coupling alignment is proposed. A monolayer SCG with high conductivity and initial anchoring of LC molecules was used as a functional electrode, thus no additional alignment layer is needed, which effectively simplifies the basic structure and process flow of conventional LCMLA. Experiments indicated that a uniform LC alignment can be acquired in the EC-LCMLA cell by the SCG coupling alignment effect. The common optical properties including focal lengths and point spread function (PSF) were measured experimentally. Experiments demonstrated that the proposed EC-LCMLA has good focusing performance in the visible to near-infrared range. Moreover, the plenoptic imaging in Galilean mode was achieved by integrating the proposed EC-LCMLA with photodetectors. Digital refocusing was performed to obtain a rendering image of the target.
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Affiliation(s)
- Mingce Chen
- National Key Laboratory of Science & Technology on Multispectral Information Processing, Huazhong University of Science & Technology, Wuhan 430074, China; (M.C.); (Q.S.); (W.H.); (D.W.); (C.H.); (J.S.); (K.L.)
- School of Artificial Intelligence and Automation, Huazhong University of Science & Technology, Wuhan 430074, China
| | - Qi Shao
- National Key Laboratory of Science & Technology on Multispectral Information Processing, Huazhong University of Science & Technology, Wuhan 430074, China; (M.C.); (Q.S.); (W.H.); (D.W.); (C.H.); (J.S.); (K.L.)
- School of Artificial Intelligence and Automation, Huazhong University of Science & Technology, Wuhan 430074, China
| | - Wenda He
- National Key Laboratory of Science & Technology on Multispectral Information Processing, Huazhong University of Science & Technology, Wuhan 430074, China; (M.C.); (Q.S.); (W.H.); (D.W.); (C.H.); (J.S.); (K.L.)
- School of Artificial Intelligence and Automation, Huazhong University of Science & Technology, Wuhan 430074, China
| | - Dong Wei
- National Key Laboratory of Science & Technology on Multispectral Information Processing, Huazhong University of Science & Technology, Wuhan 430074, China; (M.C.); (Q.S.); (W.H.); (D.W.); (C.H.); (J.S.); (K.L.)
- School of Artificial Intelligence and Automation, Huazhong University of Science & Technology, Wuhan 430074, China
| | - Chai Hu
- National Key Laboratory of Science & Technology on Multispectral Information Processing, Huazhong University of Science & Technology, Wuhan 430074, China; (M.C.); (Q.S.); (W.H.); (D.W.); (C.H.); (J.S.); (K.L.)
- School of Artificial Intelligence and Automation, Huazhong University of Science & Technology, Wuhan 430074, China
- Innovation Insititute, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Jiashuo Shi
- National Key Laboratory of Science & Technology on Multispectral Information Processing, Huazhong University of Science & Technology, Wuhan 430074, China; (M.C.); (Q.S.); (W.H.); (D.W.); (C.H.); (J.S.); (K.L.)
- School of Artificial Intelligence and Automation, Huazhong University of Science & Technology, Wuhan 430074, China
| | - Kewei Liu
- National Key Laboratory of Science & Technology on Multispectral Information Processing, Huazhong University of Science & Technology, Wuhan 430074, China; (M.C.); (Q.S.); (W.H.); (D.W.); (C.H.); (J.S.); (K.L.)
- School of Artificial Intelligence and Automation, Huazhong University of Science & Technology, Wuhan 430074, China
| | - Haiwei Wang
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science & Technology, Wuhan 430074, China; (H.W.); (C.X.)
| | - Changsheng Xie
- Wuhan National Laboratory for Optoelectronics, Huazhong University of Science & Technology, Wuhan 430074, China; (H.W.); (C.X.)
| | - Xinyu Zhang
- National Key Laboratory of Science & Technology on Multispectral Information Processing, Huazhong University of Science & Technology, Wuhan 430074, China; (M.C.); (Q.S.); (W.H.); (D.W.); (C.H.); (J.S.); (K.L.)
- School of Artificial Intelligence and Automation, Huazhong University of Science & Technology, Wuhan 430074, China
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