52 citations · 98 across the 6 of their papers we have counts for
6 papers
Adaptive information-maximization encoding for ghost imaging--A general Bayesian framework under experimental physical constraints
Jianshuo Sun, Chenyu Hu, Zunwang Bo +5
Ghost imaging (GI) has demonstrated diverse imaging capabilities enabled by its encoding-decoding-based computational imaging mechanism. Accordingly, information-theoretic studies…
Bayesian Recursive Information Optical Imaging: A Ghost Imaging Scheme Based on Bayesian Filtering
Long-Kun Du, Chenyu Hu, Shuang Liu +6
Computational imaging~(CI) has been attracting a lot of interest in recent years for its superiority over traditional imaging in various applications. In CI systems, information is…
Hyperspectral image reconstruction for spectral camera based on ghost imaging via sparsity constraints using V-DUnet
Ziyan Chen, Zhentao Liu, Chenyu Hu +6
Spectral camera based on ghost imaging via sparsity constraints (GISC spectral camera) obtains three-dimensional (3D) hyperspectral information with two-dimensional (2D) compressiv…
Spectral ghost imaging camera with super-Rayleigh modulator
Shengying Liu, Zhentao Liu, Chenyu Hu +3
A spectral camera based on ghost imaging via sparsity constraints (GISC) acquires a spectral data-cube (x; y; λ) through a single exposure. The noise immunity of the system is one…
Optimization of light fields in ghost imaging using dictionary learning
Chenyu Hu, Zhisheng Tong, Zhentao Liu +3
Ghost imaging (GI) is a novel imaging technique based on the second-order correlation of light fields. Due to limited number of samplings in practice, traditional GI methods often…
Ghost imaging LiDAR via sparsity constraints using push-broom scanning
Shuang Ma, Zhentao Liu, Chenglong Wang +7
Ghost imaging LiDAR via sparsity constraints using push-broom scanning is proposed. It can image the stationary target scene continuously along the scanning direction by taking adv…