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Lensless light-field imaging using LMI

delete2024-10-07
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OA
AI
M
Mo Chen
X
Xiaoli Liu
J
Jun Tong
J
Jiangtao Xi
Y
Yanguang Yu
Z
Zewei Cai *
DOI:10.1364/OE.539021delete
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摘要

摘要

En 中文
Light-field imaging is widely used in many fields, such as computer vision, graphics, and microscopy imaging, to record high-dimensional light information for abundant visual perception. However, light-field imaging systems generally have high system complexity and limited resolution. Over the last decades, lensless imaging systems have attracted tremendous attention to alleviate the restrictions of lens-based architectures. Despite their advantages, lensless light-field imaging introduces significant errors in light-field reconstruction. This paper introduces a novel, to our knowledge, light field moment imaging-based lensless imaging system (LMI-LIS) aiming to improve the quality of light-field reconstruction. The proposed approach first uses light field moment imaging (LMI) with a sinc angular distribution model of the light field to extract the encoded information of the scene for each sub-aperture area. Meanwhile, the corresponding sub-aperture point spread function is segmented from the system point spread function. Finally, sub-aperture images of the scene are reconstructed separately for each sub-aperture area. To evaluate the light-field reconstruction performance, the imaging quality and angular consistency of different lensless light-filed imaging methods are compared through digital refocusing, epipolar plane image, peak signal-to-noise ratio, and structural similarity index. Furthermore, the effectiveness of the proposed methodology is verified using experimental results and theoretical analysis. It is demonstrated that lensless light-field imaging using LMI and the sinc model of the angular distribution achieves high-quality sub-aperture images. (c) 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

期刊

Optics Express 封面图
Optics Express
IF:
3.3
论文数:
6.1W
被引数:
14.3W

机构

U
University of Wollongong
学者数:
1.3W
论文数: 1.6W
被引数: 2.8W
S
shenzhen university
学者数:
4.6W
论文数: 3.4W
被引数: 72
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