• Photonics Research
  • Vol. 11, Issue 3, B111 (2023)
Yunsong Lei1、2、†, Qi Zhang1、2、†, Yinghui Guo1、2, Mingbo Pu1、2, Fang Zou3, Xiong Li1、2, Xiaoliang Ma1、2, and Xiangang Luo1、2、*
Author Affiliations
  • 1State Key Laboratory of Optical Technologies on Nano-Fabrication and Micro-Engineering, Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
  • 2School of Optoelectronics, University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Tianfu Xinglong Lake Laboratory, Chengdu 610299, China
  • show less
    DOI: 10.1364/PRJ.476317 Cite this Article Set citation alerts
    Yunsong Lei, Qi Zhang, Yinghui Guo, Mingbo Pu, Fang Zou, Xiong Li, Xiaoliang Ma, Xiangang Luo. Snapshot multi-dimensional computational imaging through a liquid crystal diffuser[J]. Photonics Research, 2023, 11(3): B111 Copy Citation Text show less

    Abstract

    Multi-dimensional optical imaging systems that simultaneously gather intensity, depth, polarimetric, and spectral information have numerous applications in medical sciences, robotics, and surveillance. Nevertheless, most current approaches require mechanical moving parts or multiple modulation processes and thus suffer from long acquisition time, high system complexity, or low sampling resolution. Here, a methodology to build snapshot multi-dimensional lensless imaging is proposed by combining planar-optics and computational technology, benefiting from sufficient flexibilities in optical engineering and robust information reconstructions. Specifically, a liquid crystal diffuser based on geometric phase modulation is designed to simultaneously encode the spatial, spectral, and polarization information of an object into a snapshot detected speckle pattern. At the same time, a post-processing algorithm acts as a special decoder to recover the hidden information in the speckle with the independent and unique point spread function related to the position, wavelength, and chirality. With the merits of snapshot acquisition, multi-dimensional perception ability, simple optical configuration, and compact device size, our approach can find broad potential applications in object recognition and classification.
    Juv=[tu00tv],

    View in Article

    Jxy=M·Juv·M1=[cosθsinθsinθcosθ][tu00tv][cosθsinθsinθcosθ].

    View in Article

    [ExoutEyout]=Jxy2[1iσ]=122{(tu+tv)[1iσ]+(tutv)exp(2iσθ)[1iσ]},

    View in Article

    Pλ,σ,z=|F{A·exp[i(Φobj+ΦLC+Φsensor)]}|2,

    View in Article

    I(x,y,z,λ,σ)=O(x,y,z,λ,σ)*PSF(x,y,z,λ,σ),

    View in Article

    PSF(z1,λ1,σ1)PSF(z2,λ2,σ2){0,if|z1z2|>Tz|λ1λ2|>Tλσ1σ2δ,if  |z1z2|<Tz|λ1λ2|<Tλσ1=σ2,

    View in Article

    I=x,y,z,λ,σI(x,y,z,λ,σ)=x,y,z,λ,σ[O(x,y,z,λ,σ)*PSF(x,y,z,λ,σ)].

    View in Article

    O(x0,y0,z0,λ0,σ0)=deconv[I,PSF(x0,y0,z0,λ0,σ0)].

    View in Article

    O(x0,y0,z0,λ0,σ0)=deconv[I,PSF(x0,y0,z0,λ0,σ0)]=FFT1{FFT(I)·FFT[PSF(x0,y0,z0,λ0)]c|FFT[PSF(x0,y0,z0,λ0,σ0)]|2+SNR(f)},

    View in Article

    JI(A,B)=|AB||AB|,(A1)

    View in Article

    PCC(A,B)=cov(A,B)σAσB,(A2)

    View in Article

    Yunsong Lei, Qi Zhang, Yinghui Guo, Mingbo Pu, Fang Zou, Xiong Li, Xiaoliang Ma, Xiangang Luo. Snapshot multi-dimensional computational imaging through a liquid crystal diffuser[J]. Photonics Research, 2023, 11(3): B111
    Download Citation