arXiv subjects

Shensheng Han

Publications and source records attributed to Shensheng Han.

At least 37 records · Page 2Linked to original sources

arXiv2022

Hyperspectral image reconstruction for spectral camera based on ghost imaging via sparsity constraints using V-DUnet

Spectral camera based on ghost imaging via sparsity constraints (GISC spectral camera) obtains three-dimensional (3D) hyperspectral information with two-dimensional (2D) compressive measurements in a single shot, which has attracted much attention in recent years. However, its imaging quality and real-time performance of reconstruction still need to be further improved. Recently, deep learning has shown great potential in improving the reconstruction quality and reconstruction speed for computational imaging. When applying deep learning into GISC spectral camera, there are several challenges need to be solved: 1) how to deal with the large amount of 3D hyperspectral data, 2) how to reduce the influence caused by the uncertainty of the random reference measurements, 3) how to improve the reconstructed image quality as far as possible. In this paper, we present an end-to-end V-DUnet for the reconstruction of 3D hyperspectral data in GISC spectral camera. To reduce the influence caused by the uncertainty of the measurement matrix and enhance the reconstructed image quality, both differential ghost imaging results and the detected measurements are sent into the network's inputs. Compared with compressive sensing algorithm, such as PICHCS and TwIST, it not only significantly improves the imaging quality with high noise immunity, but also speeds up the reconstruction time by more than two orders of magnitude.

eess.IV↗

arXiv2020

Breaking Rayleigh's Criterion via Discernibility in High-Dimensional Light-Field Space with Snapshot Ghost Imaging

By encoding the high-dimensional light-field imaging information into a detectable two-dimensional speckle plane, ghost imaging camera via sparsity constraints (GISC camera) can directly catch the high-dimensional light-field imaging information with only one snapshot. This makes it worth to revisit the spatial resolution limit of this optical imaging system. In this paper we show both theoretically and experimentally that, while the resolution in high-dimensional light-field space is still limited by diffraction, the statistical spatial resolution of GISC camera can be greatly improved comparing to classical Rayleigh's criterion by utilizing the discernibility in high-dimensional light-field space. The interaction between imaging resolution, degrees of freedom of light field, and degrees of freedom of objects in high-dimensional light-field space is also demonstrated.

physics.optics↗

arXiv2020

Scattering medium: randomly packed pinhole cameras

When light travels through scattering media, speckles (spatially random distribution of fluctuated intensities) are formed due to the interference of light travelling along different optical paths, preventing the perception of structure, absolute location and dimension of a target within or on the other side of the medium. Currently, the prevailing techniques such as wavefront shaping, optical phase conjugation, scattering matrix measurement, and speckle autocorrelation imaging can only picture the target structure in the absence of prior information. Here we show that a scattering medium can be conceptualized as an assembly of randomly packed pinhole cameras, and the corresponding speckle pattern is a superposition of randomly shifted pinhole images. This provides a new perspective to bridge target, scattering medium, and speckle pattern, allowing one to localize and profile a target quantitatively from speckle patterns perceived from the other side of the scattering medium, which is impossible with all existing methods. The method also allows us to interpret some phenomena of diffusive light that are otherwise challenging to understand. For example, why the morphological appearance of speckle patterns changes with the target, why information is difficult to be extracted from thick scattering media, and what determines the capability of seeing through scattering media. In summary, the concept, whilst in its infancy, opens a new door to unveiling scattering media and information extraction from scattering media in real time.

physics.optics↗

arXiv2020

Ghost imaging based on Y-net: a dynamic coding and conjugate-decoding approach

Ghost imaging incorporating deep learning technology has recently attracted much attention in the optical imaging field. However, deterministic illumination and multiple exposure are still essential in most scenarios. Here we propose a ghost imaging scheme based on a novel conjugate-decoding deep learning framework (Y-net), which works well under both deterministic and indeterministic illumination. Benefited from the end-to-end characteristic of our network, the image of a sample can be achieved directly from a pair of correlated speckles collected by the detectors, and the sample is illuminated only once in the experiment. The spatial distribution of the speckles encoding the sample in the experiment can be completely different from that of the simulation speckles for training, as long as the statistical characteristics of the speckles remain unchanged. This approach is particularly important to high-resolution x-ray ghost imaging applications due to its potential for improving image quality and reducing radiation damage. And the idea of conjugate-decoding network may also be applied to other learning-based imaging

eess.IV↗

arXiv2019

Preconditioned Multiple Orthogonal Least Squares and Applications in Ghost Imaging via Sparsity Constraint

Ghost imaging via sparsity constraint (GISC) can recover objects from the intensity fluctuation of light fields even when the sampling rate is far below the Nyquist sampling rate. In this paper, we develop an efficient algorithm called the preconditioned multiple orthogonal least squares (PmOLS) for solving the GISC reconstruction problem. Our analysis shows that the PmOLS algorithm perfectly recovers any $n$-dimensional $K$-sparse signal from $m$ random linear samples of the signal with probability exceeding $1-3n^2 e^{-cm/K^2}$. Simulations and experiments demonstrate that the proposed algorithm has very competitive imaging quality compared to the state-ofthe-art methods.

cs.IT↗

arXiv2019

Spectral ghost imaging camera with super-Rayleigh modulator

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 of the important factors affecting the quality of the reconstructed images, especially at low sampling rates. Tailoring the intensity to generate super-Rayleigh speckle patterns which have superior noise immunity may offer an effective route to promote the imaging quality of GISC spectral camera. According to the structure of GISC spectral camera, we proposed a universal method for generating super-Rayleigh speckle patterns with customized intensity statistics based on the principle of reversibility of light. Simulation and experimental results demonstrate that, within a wide imaging spectral bandwidth, GISC spectral camera with super-Rayleigh modulator not only has superior noise immunity, but also has higher imaging quality at low sampling rates. This work will promote the application of GISC spectral camera by improving the quality of imaging results, especially in weak-light illumination.

physics.optics↗

arXiv2019

Optimization of light fields in ghost imaging using dictionary learning

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 reconstruct objects with unsatisfactory quality. To improve the imaging results, many reconstruction methods have been developed, yet the reconstruction quality is still fundamentally restricted by the modulated light fields. In this paper, we propose to improve the imaging quality of GI by optimizing the light fields, which is realized via matrix optimization for a learned dictionary incorporating the sparsity prior of objects. A closed-form solution of the sampling matrix, which enables successive sampling, is derived. Through simulation and experimental results, it is shown that the proposed scheme leads to better imaging quality compared to the state-of-the-art optimization methods for light fields, especially at a low sampling rate.

eess.IV↗

arXiv2019

Single frame wide-field Nanoscopy based on Ghost Imaging via Sparsity Constraints (GISC Nanoscopy)

The applications of present nanoscopy techniques for live cell imaging are limited by the long sampling time and low emitter density. Here we developed a new single frame wide-field nanoscopy based on ghost imaging via sparsity constraints (GISC Nanoscopy), in which a spatial random phase modulator is applied in a wide-field microscopy to achieve random measurement for fluorescence signals. This new method can effectively utilize the sparsity of fluorescence emitters to dramatically enhance the imaging resolution to 80 nm by compressive sensing (CS) reconstruction for one raw image. The ultra-high emitter density of 143 μm-2 has been achieved while the precision of single-molecule localization below 25 nm has been maintained. Thereby working with high-density of photo-switchable fluorophores GISC nanoscopy can reduce orders of magnitude sampling frames compared with previous single-molecule localization based super-resolution imaging methods.

physics.optics↗

arXiv2019

Accuracy of the semiclassical picture of photoionization in intense laser fields

In the semiclassical picture of photoionization process in intense laser fields, the ionization rate solely depends on the amplitude of the electric field and the final photoelectron momentum corresponds to the instant of ionization of the photoelectron, however, this picture has never been checked rigorously. Recently an attosecond angular streaking technique based on this semiclassical perspective has been widely applied to temporal measurement of the atomic and molecular dynamics in intense laser fields. We use a Wigner-distribution-like function to calculate the time-emission angle distribution, angular distribution and ionization time distribution for atomic ionization process in elliptically polarized few-cycle laser fields. By comparing with semiclassical calculations, we find that the two methods always show discrepancies except in some specific cases and the offset angles are generally not consistent with the offset times of the ionization time distributions obtained by the two methods even when the non-adiabatic effect is taken into account, indicating that the "attoclock" technique is in principle inaccurate. Moreover, calculations for linearly polarized laser fields also show similar discrepancies between two methods in the ionization time distribution. Our analysis indicates that the discrepancy between the semiclassical and quantum calculations can be attributed to correlation, i. e., temporal nonlocalization effect.

physics.atom-ph↗

arXiv2019

Ghost imaging LiDAR via sparsity constraints using push-broom scanning

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 advantage of the relative movement between the platform and the target scene. Compared to conventional ghost imaging LiDAR that requires multiple speckle patterns staring the target, ghost imaging LiDAR via sparsity constraints using push-broom scanning not only simplifies the imaging system, but also reduces the sampling number. Numerical simulations and experiments have demonstrated its efficiency.

eess.IV↗

arXiv2018

Lensless Wiener-Khinchin telescope based on high-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 paper, from the perspective of ghost imaging, we demonstrate for the first time to our knowledge that the point-to-point correspondence in these imaging systems can be quantitatively recovered from the high-order correlation of light fields, and the imaging capability, such as resolution, of such imaging schemes can thus be derived by analyzing high-order correlation of the optical transfer function. Based on this theoretical analysis, we propose a lensless Wiener-Khinchin telescope based on high-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, lensless Wiener-Khinchin telescope can be applied in many fields such as X-ray astronomical observations.

physics.optics↗

arXiv2018

Error-Control-Coding Assisted Imaging

Error-control-coding (ECC) techniques are widely used in modern digital communication systems to minimize the effect of noisy channels on the quality of received signals. Motivated by the fact that both communication and imaging can be considered as an information transfer process, in this paper we demonstrate that ECC could yield significant improvements in the image quality by reducing the effect of noise in the physical process of image acquisition. In the demonstrated approach, the object is encoded by ECC structured light fields generated by a digital-micromirror-device (DMD) while its image is obtained by decoding the received signal collected by a bucket-detector (BD). By applying a Luby Transform (LT) code as an example, our proof-of-concept experiment validates that the object image can be effectively reconstructed while errors induced by noisy reception can be significantly reduced. The demonstrated approach informs a new imaging technique: ECC assisted imaging, which can be scaled into applications such as remote sensing, spectroscopy and biomedical imaging.

eess.IV↗

arXiv2018

A new focal-plane 3D imaging method based on temporal ghost imaging

A new focal-plane three-dimensional (3D) imaging method based on temporal ghost imaging is proposed and demonstrated. By exploiting the advantages of temporal ghost imaging, this method enables slow integrating cameras have an ability of 3D surface imaging in the framework of sequential flood-illumination and focal-plane detection. The depth information of 3D objects is easily lost when imaging with traditional cameras, but it can be reconstructed with high-resolution by temporal correlation between received signals and reference signals. Combining with a two-dimensional (2D) projection image obtained by one single shot, a 3D image of the object can be achieved. The feasibility and performance of this focal-plane 3D imaging method have been verified through theoretical analysis and numerical experiments in this paper.

eess.IV↗

arXiv2016

Fourier-transform Ghost Imaging with Hard X-rays

Knowledge gained through X-ray crystallography fostered structural determination of materials and greatly facilitated the development of modern science and technology in the past century. Atomic details of sample structures is achievable by X-ray crystallography, however, it is only applied to crystalline structures. Imaging techniques based on X-ray coherent diffraction or zone plates are capable of resolving the internal structure of non-crystalline materials at nanoscales, but it is still a challenge to achieve atomic resolution. Here we demonstrate a novel lensless Fourier-transform ghost imaging method with pseudo-thermal hard X-rays by measuring the second-order intensity correlation function of the light. We show that high resolution Fourier-transform diffraction pattern of a complex amplitude sample can be achieved at Fresnel region and the amplitude and phase distributions of a sample in spatial domain can be retrieved successfully. The method of lensless X-ray Fourier-transform ghost imaging extends X-ray crystallography to non-crystalline samples, and its spatial resolution is limited only by the wavelength of the X-ray, thus atomic resolution should be routinely obtainable. Since highly coherent X-ray source is not required, comparing to conventional X-ray coherent diffraction imaging, the method can be implemented with laboratory X-ray sources, and it also provides a potential solution for lensless diffraction imaging with fermions, such as neutron and electron where the intensive coherent source usually is not available.

physics.optics↗

arXiv2016

Pulse-compression ghost imaging lidar via coherent detection

Ghost imaging (GI) lidar, as a novel remote sensing technique,has been receiving increasing interest in recent years. By combining pulse-compression technique and coherent detection with GI, we propose a new lidar system called pulse-compression GI lidar. Our analytical results, which are backed up by numerical simulations, demonstrate that pulse-compression GI lidar can obtain the target's spatial intensity distribution, range and moving velocity. Compared with conventional pulsed GI lidar system, pulse-compression GI lidar, without decreasing the range resolution, is easy to obtain high single pulse energy with the use of a long pulse, and the mechanism of coherent detection can eliminate the influence of the stray light, which can dramatically improve the detection sensitivity and detection range.

physics.optics↗

arXiv2016

Spectral Camera based on Ghost Imaging via Sparsity Constraints

The image information acquisition ability of a conventional camera is usually much lower than the Shannon Limit since it does not make use of the correlation between pixels of image data. Applying a random phase modulator to code the spectral images and combining with compressive sensing (CS) theory, a spectral camera based on true thermal light ghost imaging via sparsity constraints (GISC spectral camera) is proposed and demonstrated experimentally. GISC spectral camera can acquire the information at a rate significantly below the Nyquist rate, and the resolution of the cells in the three-dimensional (3D) spectral images data-cube can be achieved with a two-dimensional (2D) detector in a single exposure. For the first time, GISC spectral camera opens the way of approaching the Shannon Limit determined by Information Theory in optical imaging instruments.

physics.optics↗

arXiv2013

Three-dimensional ghost imaging ladar

Compared with two-dimensional imaging, three-dimensional imaging is much more advantageous to catch the characteristic information of the target for remote sensing. We report a range-resolving ghost imaging ladar system together with the experimental demonstration of three-dimensional remote sensing with a large field of view. The experiments show that, by measuring the correlation function of intensity fluctuations between two light fields, a three-dimensional map at about 1.0 km range with 25 cm resolution in lateral direction and 60 cm resolution in axial direction has been achieved by time-resolved measurements of the reflection signals.

quant-ph↗

arXiv2013

Single-shot Sub-Rayleigh Imaging with Sparse Detection

For conventional imaging, the imaging resolution limit is given by the Rayleigh criterion. Exploiting the prior knowledge of imaging object's sparsity and fixed optical system, imaging beyond the conventional Rayleigh limit, which is backed up by numerical simulation and experiments, is achieved by illuminating the object with single-shot thermal light and detecting the object's information at the imaging plane with some sparse-array single-pixel detectors. The quality of sub-Rayleigh imaging with sparse detection is also shown to be related to the effective number of single-pixel detectors and the detection signal-to-noise ratio at the imaging plane.

physics.optics↗