Hexagonal diffractive optical elements

被引:0
作者
Zheng, Yidan [1 ]
Fu, Qiang [1 ]
Amata, Hadi [1 ]
Chakravarthula, Praneeth [2 ]
Heide, Felix [2 ]
Heidrich, Wolfgang [1 ]
机构
[1] King Abdullah Univ Sci & Technol KAUST, Thuwal 239556900, Saudi Arabia
[2] Princeton Univ, Dept Comp Sci, Princeton, NJ 08544 USA
关键词
RECONSTRUCTION; FABRICATION; IMAGE; PHASE;
D O I
暂无
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Diffractive optical elements (DOEs) have widespread applications in optics, ranging from point spread function engineering to holographic display. Conventionally, DOE design relies on Cartesian simulation grids, resulting in square features in the final design. Unfortunately, Cartesian grids provide an anisotropic sampling of the plane, and the resulting square features can be challenging to fabricate with high fidelity using methods such as photolithography. To address these limitations, we explore the use of hexagonal grids as a new grid structure for DOE design and fabrication. In this study, we demonstrate wave propagation simulation using an efficient hexagonal coordinate system and compare simulation accuracy with the standard Cartesian sampling scheme. Additionally, we have implemented algorithms for the inverse DOE design. The resulting hexagonal DOEs, encoded with wavefront information for holograms, are fabricated and experimentally compared to their Cartesian counterparts. Our findings indicate that employing hexagonal grids enhances holographic imaging quality. The exploration of new grid structures holds significant potential for advancing optical technology across various domains, including imaging, microscopy, photography, lighting, and virtual reality. (c) 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
引用
收藏
页码:43864 / 43876
页数:13
相关论文
共 36 条
[1]  
Aiazzi B., 2002, 11 EUROPEAN SIGNAL P, P1
[2]   BACKPROPAGATION AND STOCHASTIC GRADIENT DESCENT METHOD [J].
AMARI, S .
NEUROCOMPUTING, 1993, 5 (4-5) :185-196
[3]   Single-shot Hyperspectral-Depth Imaging with Learned Diffractive Optics [J].
Baek, Seung-Hwan ;
Ikoma, Hayato ;
Jeon, Daniel S. ;
Li, Yuqi ;
Heidrich, Wolfgang ;
Wetzstein, Gordon ;
Kim, Min H. .
2021 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2021), 2021, :2631-2640
[4]  
Birdsong JB, 2016, IEEE IMAGE PROC, P1809, DOI 10.1109/ICIP.2016.7532670
[5]   TREE AND PYRAMID STRUCTURES FOR CODING HEXAGONALLY SAMPLED BINARY IMAGES [J].
BURT, PJ .
COMPUTER GRAPHICS AND IMAGE PROCESSING, 1980, 14 (03) :271-280
[6]  
Burton II J. C., 1993, End-to-end Analysis of Hexagonal vs. Rectangular Sampling in Digital Imaging Systems
[7]   Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification [J].
Chang, Julie ;
Sitzmann, Vincent ;
Dun, Xiong ;
Heidrich, Wolfgang ;
Wetzstein, Gordon .
SCIENTIFIC REPORTS, 2018, 8
[8]   Resolution comparison between integral-imaging-based hologram synthesis methods using rectangular and hexagonal lens arrays [J].
Chen, Ni ;
Yeom, Jiwoon ;
Jung, Jae-Hyun ;
Park, Jae-Hyeung ;
Lee, Byoungho .
OPTICS EXPRESS, 2011, 19 (27) :26917-26927
[9]   Wiener index of hexagonal systems [J].
Dobrynin, AA ;
Gutman, I ;
Klavzar, S ;
Zigert, P .
ACTA APPLICANDAE MATHEMATICAE, 2002, 72 (03) :247-294
[10]  
Engl H. W., 1996, Regularization of inverse problems, V375