Lensless light-field imaging using LMI

被引:1
作者
Mo, Chen [1 ,2 ]
Liu, Xiaoli [1 ]
Tong, Jun [2 ]
Xi, Jiangtao [2 ]
Yu, Yanguang [2 ]
Cai, Zewei [1 ]
机构
[1] Shenzhen Univ, Coll Phys & Optoelect Engn, Key Lab Optoelect Devices & Syst, Minist Educ & Guangdong Prov, Shenzhen 518060, Peoples R China
[2] Univ Wollongong, Sch Elect Comp & Telecommun Engn, Wollongong, NSW 2522, Australia
基金
中国国家自然科学基金;
关键词
Angular distribution - Lenses;
D O I
10.1364/OE.539021
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
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
引用
收藏
页码:38112 / 38127
页数:16
相关论文
共 36 条
[1]  
Adelson EH, 1991, COMPUTATIONAL MODELS, P3, DOI DOI 10.7551/MITPRESS/2002.003.0004
[2]  
Antipa N., 2017, IMAGING APPL OPTICS
[3]  
Antipa N., 2017, Computational Optical Sensing and Imaging
[4]  
Antipa N, 2016, IEEE INT CONF COMPUT, P134
[5]   Video from Stills: Lensless Imaging with Rolling Shutter [J].
Antipa, Nick ;
Oare, Patrick ;
Bostan, Emrah ;
Ng, Ren ;
Waller, Laura .
2019 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL PHOTOGRAPHY (ICCP), 2019,
[6]   DiffuserCam: lensless single-exposure 3D imaging [J].
Antipa, Nick ;
Kuo, Grace ;
Heckel, Reinhard ;
Mildenhall, Ben ;
Bostan, Emrah ;
Ng, Ren ;
Waller, Laura .
OPTICA, 2018, 5 (01) :1-9
[7]  
Bass M., 1995, Handbook of Optics, V1
[8]  
Boominathan V, 2022, OPTICA, V9, P1, DOI [10.1364/optica.431361, 10.1364/OPTICA.431361]
[9]   PhlatCam: Designed Phase-Mask Based Thin Lensless Camera [J].
Boominathan, Vivek ;
Adams, Jesse K. ;
Robinson, Jacob T. ;
Veeraraghavan, Ashok .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 42 (07) :1618-1629
[10]   Lensless light-field imaging through diffuser encoding [J].
Cai, Zewei ;
Chen, Jiawei ;
Pedrini, Giancarlo ;
Osten, Wolfgang ;
Liu, Xiaoli ;
Peng, Xiang .
LIGHT-SCIENCE & APPLICATIONS, 2020, 9 (01)