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| 1 | Ghost imaging for an axially moving target with an unknown constant speed显示文摘The influence of the axial relative motion between the target and the source on ghost imaging(GI) is investigated.Both the analytical and experimental results show that the transverse resolution of GI is reduced as the deviation of the target’s center position from the optical axis or the axial motion range increases. To overcome the motion blur,we propose a deblurring method based on speckle-resizing and speed retrieval, and we experimentally validate its effectiveness for an axially moving target with an unknown constant speed. The results demonstrated here will be very useful to forward-looking GI remote sensing. | Xiaohui Li Chenjin Deng Mingliang Chen Wenlin Gong Shensheng Han | 2015 | Photonics Research2015，3，4： | 15 |
| 2 | Performance analysis of ghost imaging lidar in background light environment显示文摘The effect of background light on the imaging quality of three typical ghost imaging(GI) lidar systems(namely narrow pulsed GI lidar, heterodyne GI lidar, and pulse-compression GI lidar via coherent detection) is investigated. By computing the signal-to-noise ratio(SNR) of fluctuation-correlation GI, our analytical results, which are backed up by numerical simulations, demonstrate that pulse-compression GI lidar via coherent detection has the strongest capacity against background light, whereas the reconstruction quality of narrow pulsed GI lidar is the most vulnerable to background light. The relationship between the peak SNR of the reconstruction image andσ(namely, the signal power to background power ratio) for the three GI lidar systems is also presented, and theresults accord with the curve of SNR-σ. | CHENJIN DENG LONG PAN CHENGLONG WANG XIN GAO WENLIN GONG SHENSHENG HAN | 2017 | Photonics Research2017，5，5： | 13 |
| 3 | Physical picture of the optical memory effect显示文摘The optical memory effect is an interesting phenomenon that has attracted considerable attention in recent decades. Here, we present a new physical picture of the optical memory effect, in which the memory effect and the conventional spatial shift invariance are united. Based on this picture we depict the role of thickness, scattering times, and anisotropy factor and derive equations to calculate the ranges of the angular memory effect(AME) of different scattering components(ballistic light, singly scattered, doubly scattered, etc.), and hence a more accurate equation for the real AME ranges of volumetric turbid media. A conventional random phase mask model is modified according to the new picture. The self-consistency of the simulation model and its agreement with the experiment demonstrate the rationality of the model and the physical picture, which provide powerful tools for more sophisticated studies of the memory-effect-related phenomena and wavefront-sensitive techniques, such as wavefront shaping, optical phase conjugation, and optical trapping in/through scattering media. | Honglin Liu Zhentao Liu Meijun Chen Shensheng Han Lihong V.Wang | 2019 | Photonics Research2019，7，11： | 9 |
| 4 | Far-field super-resolution ghost imaging with a deep neural network constraint显示文摘Ghost imaging(GI)facilitates image acquisition under low-light conditions by single-pixel measurements and thus has great potential in applications in various fields ranging from biomedical imaging to remote sensing.However,GI usually requires a large amount of single-pixel samplings in order to reconstruct a high-resolution image,imposing a practical limit for its applications.Here we propose a far-field super-resolution GI technique that incorporates the physical model for GI image formation into a deep neural network.The resulting hybrid neural network does not need to pre-train on any dataset,and allows the reconstruction of a far-field image with the resolution beyond the diffraction limit.Furthermore,the physical model imposes a constraint to the network output,making it effectively interpretable.We experimentally demonstrate the proposed GI technique by imaging a flying drone,and show that it outperforms some other widespread GI techniques in terms of both spatial resolution and sampling ratio.We believe that this study provides a new framework for GI,and paves a way for its practical applications. | Fei Wang Chenglong Wang Mingliang Chen Wenlin Gong Yu Zhang Shensheng Han Guohai Situ | 2022 | Light(Science & Applications)2022，11，1： | 6 |
| 5 | Preconditioned deconvolution method for high-resolution ghost imaging显示文摘Ghost imaging(GI)can nonlocally image objects by exploiting the fluctuation characteristics of light fields,where the spatial resolution is determined by the normalized second-order correlation function g^(2) .However,the spatial shift-invariant property of g^(2) is distorted when the number of samples is limited,which hinders the deconvolution methods from improving the spatial resolution of GI.In this paper,based on prior imaging systems,we propose a preconditioned deconvolution method to improve the imaging resolution of GI by refining the mutual coherence of a sampling matrix in GI.Our theoretical analysis shows that the preconditioned deconvolution method actually extends the deconvolution technique to GI and regresses into the classical deconvolution technique for the conventional imaging system.The imaging resolution of GI after preconditioning is restricted to the detection noise.Both simulation and experimental results show that the spatial resolution of the reconstructed image is obviously enhanced by using the preconditioned deconvolution method.In the experiment,1.4-fold resolution enhancement over Rayleigh criterion is achieved via the preconditioned deconvolution.Our results extend the deconvolution technique that is only applicable to spatial shift-invariant imaging systems to all linear imaging systems,and will promote their applications in biological imaging and remote sensing for high-resolution imaging demands. | ZHISHEN TONG ZHENTAO LIU CHENYU HU JIAN WANG SHENSHENG HAN | 2021 | Photonics Research2021，9，6： | 5 |
| 6 | Deep plug-and-play priors for spectral snapshot compressive imaging显示文摘We propose a plug-and-play(Pn P) method that uses deep-learning-based denoisers as regularization priors for spectral snapshot compressive imaging(SCI). Our method is efficient in terms of reconstruction quality and speed trade-off, and flexible enough to be ready to use for different compressive coding mechanisms. We demonstrate the efficiency and flexibility in both simulations and five different spectral SCI systems and show that the proposed deep Pn P prior could achieve state-of-the-art results with a simple plug-in based on the optimization framework. This paves the way for capturing and recovering multi-or hyperspectral information in one snapshot,which might inspire intriguing applications in remote sensing, biomedical science, and material science. Our code is available at: https://github.com/zsm1211/Pn P-CASSI. | SIMING ZHENG YANG LIU ZIYI MENG MU QIAO ZHISHEN TONG XIAOYU YANG SHENSHENG HAN XIN YUAN | 2021 | Photonics Research2021，9，2： | 4 |
| 7 | Single-pixel neutron imaging with artificial intelligence: Breaking the barrier in multi-parameter imaging, sensitivity, and spatial resolution显示文摘Different from X-rays,neutrons mainly interact with atomic nuclei and magnetic moments in materials.This makes neutron imaging a complementary contrast mechanism to X-ray imaging.Neutron imaging aims to infer the internal material information of the object by measuring the changes in neutron beam parameters,such as the intensity attenuation,polarization,scattering,and matter wave interference.It has a wide range of applications in industry such as the inspection of batteries,magnetic structure analysis,and strain mapping in alloys. | Xin Yuan Shensheng Han | 2021 | The Innovation2021，2，2： | 3 |
| 8 | Single-pixel imaging using physics enhanced deep learning显示文摘Single-pixel imaging(SPI) is a typical computational imaging modality that allows two-and three-dimensional image reconstruction from a one-dimensional bucket signal acquired under structured illumination.It is in particular of interest for imaging under low light conditions and in spectral regions where good cameras are unavailable.However,the resolution of the reconstructed image in SPI is strongly dependent on the number of measurements in the temporal domain.Data-driven deep learning has been proposed for high-quality image reconstruction from a undersampled bucket signal.But the generalization issue prohibits its practical application.Here we propose a physics-enhanced deep learning approach for SPI.By blending a physics-informed layer and a model-driven fine-tuning process,we show that the proposed approach is generalizable for image reconstruction.We implement the proposed method in an in-house SPI system and an outdoor single-pixel LiDAR system,and demonstrate that it outperforms some other widespread SPI algorithms in terms of both robustness and fidelity.The proposed method establishes a bridge between data-driven and model-driven algorithms,allowing one to impose both data and physics priors for inverse problem solvers in computational imaging,ranging from remote sensing to microscopy. | FEI WANG CHENGLONG WANG CHENJIN DENG SHENSHENG HAN GUOHAI SITU | 2022 | Photonics Research2022，10，1： | 2 |
| 9 | A FAST CONVERGING SPARSE RECONSTRUCTION ALGORITHM IN GHOST IMAGING显示文摘A fast converging sparse reconstruction algorithm in ghost imaging is presented. It utilizes total variation regularization and its formulation is based on the Karush-Kuhn-Tucker (KKT) theorem in the theory of convex optimization. Tests using experimental data show that, compared with the algorithm of Gradient Projection for Sparse Reconstruction (GPSR), the proposed algorithm yields better results with less computation work. | Li Enrong Chen Mingliang Gong Wenlin Wang Hui Han Shensheng | 2012 | Journal of Electronics(China)2012，29，6： | 2 |
| 10 | Phase-retrieval ghost imaging of complex-valued objects显示文摘 | Gong Wenlin Han Shensheng | 2010 | Physi- cal Review A2010，82，02： | 1 |
| 11 | Incoherent coincidence imaging and its applicability in X-ray diffraction 显示文摘 | Jing Cheng Shensheng Han | 2004 | Phys Rev Lett2004，92，09： | 1 |
| 12 | Lens ghost imaging with thermal light: from the far field to the near field 显示文摘 | Wenlin Gong Shensheng Han | 2010 | Phys Lett A2010，374，36： | 1 |
| 13 | Incoherent Coincidence Imaging and Its Applicability in X-ray Diffraction显示文摘 | Jing Cheng Shensheng Han | 2004 | Phys Rev Lett2004，92，93： | 1 |
| 14 | Alternative Interpretation of Speckle Autocorrelation Imaging Through Scattering Media显示文摘High-resolution optical imaging through or within thick scattering media is a long sought after yet unreached goal.In the past decade,the thriving technique developments in wavefront measurement and manipulation do not significantly push the boundary forward.The optical diffusion limit is still a ceiling.In this work,we propose that a scattering medium can be conceptualized as an assembly of randomly packed pinhole cameras and the corresponding speckle pattern as a superposition of randomly shifted pinhole images.The concept is demonstrated through both simulation and experiments,confirming the new perspective to interpret the mechanism of information transmission through scattering media under incoherent illumination.We also analyze the efficiency of single-pinhole and dual-pinhole channels.While in infancy,the proposed method reveals a new perspective to understand imaging and information transmission through scattering media. | Honglin LIU Puxiang LAI Jingjing GAO Zhentao LIU Jianhong SHI Shensheng HAN | 2022 | Photonic Sensors2022，12，3： | 1 |
| 15 | Correlated imaging in scattering media 显示文摘 | Wenlin Gong Shensheng Han | 2011 | Opt Lett2011，36，3： | 1 |
| 16 | Incoherent coincidence imaging and its applicability in x-ray diffraction 显示文摘 | CHENG Jing HAN Shensheng | 2004 | Phys Rev Lett2004，92，09： | 1 |
| 17 | Correlated Imaging in Scattering Media 显示文摘 | Wenlin Gong Shensheng Han | 2011 | Optics Letters2011，36，： | 1 |
| 18 | Incoherent coincidence imaging and its applicability in X-ray diffraction显示文摘 | Jing Cheng Shensheng Han | 2004 | Phys Rev Lett2004，92，9： | 1 |
| 19 | Correlated imaging in scattering media显示文摘 | Wenlin Gong Shensheng Han | 2011 | Opt Lett2011，36，3： | 1 |
| 20 | A method to improve the visibility of ghost images obtained by thermal light显示文摘 | Wenlin Gong Shensheng Han | 2010 | Phys Lett A2010，374，8： | 1 |
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