Ghost Imaging Lidar via Sparsity Constraints in Real Atmosphere

We present a series of results acquired at a 2-kilometer distance using our lidar system under several weather conditions, clear, cloudy, light rain, moderately foggy, and night. The experimental results show that ghost imaging lidar via spar-sity constraints can realize imaging in all these weather conditions.

Wide-spectrum optical synthetic aperture imaging via spatial intensity interferometry

High resolution imaging is achieved using increasingly larger apertures and successively shorter wavelengths.Optical aperture synthesis is an important high-resolution imaging technology used in astronomy.Conventional long baseline amplitude interferometry is susceptible to uncontrollable phase fluctuations,and the technical difficulty increases rapidly as the wavelength decreases.The intensity interferometry inspired by HBT experiment is essentially insensitive to phase fluctuations,but suffers from a narrow spectral bandwidth which results in a lack of effective photons.In this study,we propose optical synthetic aperture imaging based on spatial intensity interferometry.This not only realizes diffraction-limited optical aperture synthesis in a single shot,but also enables imaging with a wide spectral bandwidth,which greatly improves the optical energy efficiency of intensity interferometry.And this method is insensitive to the optical path difference between the sub-apertures.Simulations and experiments present optical aperture synthesis diffraction-limited imaging through spatial intensity interferometry in a 100 nm spectral width of visible light,whose maximum optical path difference between the sub-apertures reaches 69λ.This technique is expected to provide a solution for optical aperture synthesis over kilometer-long baselines at optical wavelengths.

Seeing through dynamics scattering media:Suppressing diffused reflection based on decorrelation time difference

We observed a phenomenon that different scattering components have different decorrelation time.Based on decorrelation time difference,we proposed a method to image an object hidden behind a turbid medium in a reflection mode.In order to suppress the big disturbance calused by reflection and back scattering,two framnes of speckles are recorded in sequence,and their difference is used for image reconstruction.Our method is immune to both medium motions and object movements.

Single-pixel imaging using physics enhanced deep learning

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.

Different channels to transmit information in scattering media

A communication channel should be built to transmit information from one place to another.Imaging is 2 or higher dimensional information communication.Conventionally,an imaging channel comprises a lens with free space at its both sides,whose transfer function is usually known and hence the response of the imaging channel can be well defined.Replacing the lens with a thin scattering medium,the image can still be extracted from the detected optical field,suggesting that the scattering medium retains or reconstructs not only energy but also information transmission channels.Aided by deep learning,we find that unlike the lens system,there are different channels in a scattering medium:the same scattering medium can construct different channels to match the manners of source coding.Moreover,it is found that without a valid channel,the convolution law for a spatial shift-invariant system(the output is the convolution of the point spread function and the input object)is broken,and in this scenario,information cannot be transmitted onto the detection plane.Therefore,valid channels are essential to transmit information through even a spatial shift-invariant system.These findings may intrigue new adventures in imaging through scattering media and reevaluation of the known spatial shift-invariance in various areas.

Editorial of special issue on quantum imaging

Quantum detection technology and quantum imaging based on two-photon interference effects, along with various new conceptual imaging schemes inspired by the two-photon interference quantum imaging, have significantly redefined the sight and content of imaging technology. This has rejuvenated the ancient discipline of imaging science, transforming it into a burgeoning field at the intersection of statistical and quantum optics, information science, applied mathematics, artificial intelligence, computer vision, light field manipulation technology, and compressive sensing technology. These advancements provide practical and innovative technological approaches to greatly enhance the capability and efficiency of image information acquisition in various application scenarios.Profs.

Far-field super-resolution ghost imaging with a deep neural network constraint

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.

Physical picture of the optical memory effect

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.

Performance analysis of ghost imaging lidar in background light environment

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.

Ghost imaging for an axially moving target with an unknown constant speed

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.

Alternative Interpretation of Speckle Autocorrelation Imaging Through Scattering Media

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.

Deep plug-and-play priors for spectral snapshot compressive imaging

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.

Preconditioned deconvolution method for high-resolution ghost imaging

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.

Color ghost imaging via sparsity constraint and non-local self-similarity

We propose a color ghost imaging approach where the object is illuminated by three-color non-orthogonal random patterns. The object’s reflection/transmission information is received by only one single-pixel detector, and both the sparsity constraint and non-local self-similarity of the object are utilized in the image reconstruction process. Numerical simulation results demonstrate that the imaging quality can be obviously enhanced by ghost imaging via sparsity constraint and nonlocal self-similarity(GISCNL), compared with the reconstruction methods where only the object’s sparsity is used. Factors affecting the quality of GISCNL, such as the measurement number and the detection signal-to-noise ratio, are also studied.

Lensless Wiener–Khinchin telescope based on second-order spatial autocorrelation of thermal light

The resolution of a conventional imaging system based on first-order field correlation can be directly obtained from the optical transfer function. However, it is challenging to determine the resolution of an imaging system through random media, including imaging through scattering media and imaging through randomly inhomogeneous media, since the point-to-point correspondence between the object and the image plane in these systems cannot be established by the first-order field correlation anymore. In this Letter, from the perspective of ghost imaging, we demonstrate for the first time, to the best of our knowledge, that the point-to-point correspondence in these imaging systems can be quantitatively recovered from the second-order correlation of light fields, and the imaging capability, such as resolution, of such imaging schemes can thus be derived by analyzing second-order autocorrelation of the optical transfer function. Based on this theoretical analysis, we propose a lensless Wiener–Khinchin telescope based on second-order spatial autocorrelation of thermal light, which can acquire the image of an object by a snapshot via using a spatial random phase modulator. As an incoherent imaging approach illuminated by thermal light, the lensless Wiener–Khinchin telescope can be applied in many fields such as X-ray astronomical observations.

Time-energy analysis of the photoionization process in a double-XUV pulse combined with a few-cycle IR field

We calculate the time-energy distribution(TED)and ionization time distribution(ITD)of photoelectrons emitted by a doubleextreme-ultraviolet(XUV)pulse and a two-color XUV-IR pulse using the Wigner distribution-like function based on the strong field approximation.For a double-XUV pulse,besides two identical broad distributions generated by two XUV pulses,many interference fringes resulting from the interference between electrons generated,respectively,by two pulses appear in the TED.After adding an IR field,the TED intuitively exhibits the effect of the IR field on the electron dynamics.The ITDs during two XUV pulses are no longer the same and show the different changes for the different two-color fields,the origin of which is attributed to the change of the electric field induced by the IR field.Our analysis shows that the emission time of electrons ionized during two XUV pulses mainly depends on the electric field of the combined XUV pulse and IR pulse.

Influence of the sparsity of random speckle illumination on ghost imaging in a noise environment

The influence of the sparsity of random speckle illumination on traditional ghost imaging(GI) and GI via sparsity constraint(GISC) in a noise environment is investigated. The experiments demonstrate that both GI and GISC obtain their best imaging quality when the sparsity of random speckle illumination is 0.5, which is also explained by some parameters such as detection of the signal to noise ratio and mutual coherence of the measurement matrix.

Megapixel X-ray ghost imaging with a binned detector in the object arm

At present,reconstruction of megapixel and high-fidelity images with few measurements is a major challenge for X-ray ghost imaging(XGI).The available strategies require massive measurements and reconstruct low-fidelity images of less than 300 × 300 pixels.Inspired by the concept of synthetic aperture radar,synthetic aperture XGI(SAXGI)integrated with compressive sensing is proposed to solve this problem with a binned detector in the object arm.Experimental results demonstrated that SAXGI can accurately reconstruct the 1200 × 1200 pixels image of a binary sample of tangled strands of tungsten fiber from 660 measurements.Accordingly,SAXGI is a promising solution for the practical application of XGI.

Imaging through dynamic scattering media with stitched speckle patterns

Imaging through scattering media via speckle autocorrelation is a popular method based on the optical memory effect.However,it fails if the amount of valid information acquired is insufficient due to a limited sensor size.In this Letter,we reveal a relationship between the detector and object sizes for the minimum requirement to ensure image reconstruction by defining a sampling ratio R,and propose a method to enhance the image quality at a small R by capturing multiple frames of speckle patterns and piecing them together.This method will be helpful in expanding applications of speckle autocorrelation to remote sensing,underwater probing,and so on.

Influence of the source’s energy fluctuation on computational ghost imaging and effective correction approaches

We investigate the influence of the source’s energy fluctuation on both computational ghost imaging and computational ghost imaging via sparsity constraint,and if the reconstruction quality will decrease with the increase of the source’s energy fluctuation.In order to overcome the problem of image degradation,a correction approach against the source’s energy fluctuation is proposed by recording the source’s fluctuation with a monitor before modulation and correcting the echo signal or the intensity of computed reference light field with the data recorded by the monitor.Both the numerical simulation and experimental results demonstrate that computational ghost imaging via sparsity constraint can be enhanced by correcting the echo signal or the intensity of computed reference light field,while only correcting the echo signal is valid for computational ghost imaging.