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Proceedings Paper

Autofocusing imaging based on electrically controlled liquid-crystal microlens array
Author(s): Wenda He; Qi Shao; Jinxing Liu; Mingce Chen; Xinyu Zhang
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Paper Abstract

As an effective method for collecting light field information and further extending the depth of field, a new imaging technology based on key electrically controlled liquid-crystal microlens array (EC-LCMLA), has been proposed. Compared with common lenses with defined surface profile, the liquid-crystal microlenses can be used to regulate the focal length only through applying different signal voltages to achieve focus tuning or even swing on the observation plane. Generally, the traditional autofocus operations are no longer suitable to EC-LCMLA because the controlling orders for LC structures should be generated through image process. So, an autofocus method, which is used to dynamically adjust the focal length of each imaging unit in the EC-MLA, is proposed for controlled LCMLA in this paper. The method is used to extract the light field information from low-quality image, so as to obtain the key focusing distance of the plane observed by each imaging unit, and then calculate the focal length of the EC-LCMLA without additional sensors. The signal voltage of each liquid-crystal microlens can be adjusted by the driving control unit, which implements an automatic focusing of the LCMLA. The active autofocus therefore is achieved and then all the imaging units in an optimal working state. Based on theoretical analysis and the focusing algorithm constructed by us, the imaging experiments are carried out so as to show a higher performance and then image quality and focusing efficiency of LCMLA. The novel autofocus method highlights a construction of a new kind of plenoptic camera with stronger performances.

Paper Details

Date Published: 14 February 2020
PDF: 4 pages
Proc. SPIE 11428, MIPPR 2019: Multispectral Image Acquisition, Processing, and Analysis, 1142803 (14 February 2020); doi: 10.1117/12.2537509
Show Author Affiliations
Wenda He, Huazhong Univ. of Science and Technology (China)
Qi Shao, Huazhong Univ. of Science and Technology (China)
Jinxing Liu, Huazhong Univ. of Science and Technology (China)
Mingce Chen, Huazhong Univ. of Science and Technology (China)
Xinyu Zhang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11428:
MIPPR 2019: Multispectral Image Acquisition, Processing, and Analysis
Xinyu Zhang; Chao Pan; Hongshi Sang, Editor(s)

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