Computational Ghost Imaging Research Articles

ADMM algorithm for Computational ghost imaging using Hadamard derivative pattern

Aiming at the problems of long reconstruction time, high sampling rate and poor imaging effect caused by traditional illumination speckle in ghost imaging reconstruction, this paper proposes to use ordered orthogonal Hadamard derived speckle as the illumination speckle series of ghost imaging to reduce the measurement times and improve the quality of reconstructed images. In addition, the alternate direction multiplier method is introduced into the image reconstruction algorithm to further improve the imaging performance of ghost imaging. Finally, the method used in this paper is evaluated objectively, and the evaluation results show that the combination of Hadamard derived speckle and alternating direction multiplication has better imaging effect, and can obtain high-quality reconstructed images under low sampling conditions. It is expected that this method can be applied to target detection and recognition, improve detection and recognition ability, and help users get more useful information.

Anti-scattering medium computational ghost imaging with modified Hadamard patterns

Illumination patterns of computational ghost imaging (CGI) systems suffer from reduced contrast when passing through a scattering medium, which causes the effective information in the reconstruction result to be drowned out by noise. A two-dimensional (2D) Gaussian filter performs linear smoothing operation on the whole image for image denoising. It can be combined with linear reconstruction algorithms of CGI to obtain the noise-reduced results directly, without post-processing. However, it results in blurred image edges while performing denoising and, in addition, a suitable standard deviation is difficult to choose in advance, especially in an unknown scattering environment. In this work, we subtly exploit the characteristics of CGI to solve these two problems very well. A kind of modified Hadamard pattern based on the 2D Gaussian filter and the differential operation features of Hadamard-based CGI is developed. We analyze and demonstrate experimentally that using Hadamard patterns for illumination but using our developed modified Hadamard patterns for reconstruction (MHCGI) can enhance the robustness of CGI against turbid scattering medium. Our method not only helps directly obtain noise-reduced results without blurred edges but also requires only an approximate standard deviation, i.e., it can be set in advance. The experimental results on transmitted and reflected targets demonstrate the feasibility of our method. Our method helps to promote the practical application of CGI in the scattering environment.

High-quality computational ghost imaging with multi-scale light fields optimization

High-quality computational ghost imaging under low sampling rates has always attracted much attention and plays an important role in practical applications. In this paper, a novel optical field optimization method based on multi-scale light fields singular value decomposition which can greatly reduce the number of computational ghost imaging measurements is proposed. The computational ghost imaging measurement matrix is derived from the components obtained by singular value decomposition of self-designed special measurement matrices. When the measurement matrix is fully sampled, high-quality reconstructed image can be obtained. Similarly, when the measurement matrix is under-sampled, it is still possible to obtain high-quality reconstructed image and show the performance of multi-resolution imaging. Simulation and experimental results show that our method can obtain high-quality computational ghost imaging, even at low sampling rates, and as the number of splicing matrices increases, the number of measurements is further reduced.

Parallel multispectral ghost imaging data acquisition with supercontinuum

A wavelength multiplexing with spectral supercontinuum source in computational ghost imaging is implemented and investigated. In our proof-of-concept experiment, we used two diffraction gratings and one spatial light modulator to form up to 10 independent spectral channels. Registration of data by a spectrometer in such a scheme makes it possible to reduce the time of data acquisition by a factor of ten. It was established that an increase the number of spectral channels from 1 to 10 leads to the increase of the contrast-to-noise ratio by the factor of 2.8. This makes the proposed technique attractive for high-speed demanding applications such as communications and remote sensing.

Optical authentication method based on correspondence ghost imaging.

Ghost imaging technology has a great application potential in optical security because of its non-local characteristics. In this paper, on the basis of computational ghost imaging, an optical authentication scheme is proposed that utilizes the correspondence imaging technique for the preliminary reconstruction of the object image, and then authenticates the image by a nonlinear correlation algorithm. Different from the previous optical authentication schemes that usually adopted random selection of measurements, this authentication method consciously selects the bucket detector measurement values with large fluctuation and can achieve authentication using ultra-low data volumes less than 1% of the Nyquist limit. In brief, this scheme is easy to implement and has a simpler algorithm and higher stability, which is a tremendous advantage in practical optical authentication systems. The simulation and physical experimental results demonstrate the feasibility of the scheme.

BM3D-based color computational ghost imaging

In this study, we develop a BM3D-based algorithm to improve the performance of color computational ghost imaging. Specifically, we respectively project the speckle patterns of red, green and blue onto the object. Then, we adopt the single-pixel photodetector to record the total light intensity reflected by the target object. Finally, we calculate the correlation between the light intensity sequence and the corresponding speckle patterns based on BM3D algorithm. Our simulation results show that the developed scheme can achieve high-quality reconstruction image even at low sampling ratio.

Polarized computational ghost imaging in scattering system with half-cyclic sinusoidal patterns

Computational Ghost Imaging (CGI) can reconstruct the scene images through the correlation algorithm between the preset illumination patterns and the intensities of the detection bucket detector. In the actual transmission process, the scattering system in the imaging path can affect the imaging quality of the CGI. The half-cyclic sinusoidal-pattern based CGI (HCSP-CGI) can recover the scene images at low sampling rates (SRs). Based on the Monte Carlo (MC) model, we propose and construct a reflective polarization system based the HCSP-CGI in fog environment and put forward a method that combines polarization information with the HCSP-CGI called the PHCSP-CGI. When the difference in reflectivity between target and background is small, the difference in polarization characteristics between target and background can help CGI to remove the interference of stray light. The imaging performance of the PHCSP-CGI at different SRs and scattering distances (SDs) are analyzed. Experimental results show that high-contrast scene can still be obtained, providing new applications for object recognition in scattering system.

Detecting Angle of Arrival on a Hybrid RIS Using Intensity-Only Data

Reconfigurable reflective metasurfaces—or reconfigurable intelligent surfaces (RISs)—can redirect incident signals toward desired directions, an ability that allows for sculpting wireless communication channels with desired characteristics. This smart radio environment, however, necessitates the information about the transmitter(s) and the receiver(s) to be available at the RIS. One possible solution to this need is to add sensing capability to the RIS. However, sensing complex wireless signals (i.e. both amplitude and phase) often requires complicated setups. In this paper, we propose and numerically demonstrate a reconfigurable reflective metasurface that uses intensity-only samples of the incident signal to retrieve desired information about the propagation environment. To do that, we will randomly tune the metasurface elements to multiplex information incident on all of them. The phaseless multiplexed data is then processed using computational ghost imaging algorithm to retrieve the desired information. As a demonstrative example, we present the detection of the incident angle from a user in a free-space environment. This simplified sensing process can pave the way for incorporation of RISs with integrated sensing capabilities in future wireless communication or sensing systems.

Research on mechanism of joint-coding imaging based on generative adversarial neural network

In the previous research of ghost imaging schemes based on joint-coding technology, to ensure the imaging quality, it is often carried out under the premise of full sampling or even super-sampling, which undoubtedly requires a long sampling time. In this paper, a joint coding imaging scheme based on the generative adversarial neural network is proposed. By introducing the generative adversarial neural network, the image is reconstructed under half sampling, which greatly saves the sampling time. At the same time, the joint coding technology is incorporated to ensure the imaging quality of the computational ghost imaging scheme. Comparison through experimental, it can be proved that the imaging quality of this scheme under half sampling can achieve the imaging effect of CSGI algorithm under full sampling, and in the case of different signal-to-noise ratio noise, the reconstruction of our scheme has stronger robustness compared with other schemes. Briefly our scheme provides a new imaging technology for the research in the imaging field, which has good theoretical significance.

Effect of the ratio of black speckle on computational ghost imaging

The effect of the ratio of black speckles on computational ghost imaging has been investigated. However, the experimental results are inconsistent with the existing theoretical results. During the imaging process with strong background noise, the image quality is not optimal when the black speckle ratio is 50%. On the contrary, the experimental results indicate that increasing the black speckle ratio can enhance the contrast-to-noise ratio and reduce the correlation calculation time. This phenomenon occurs because, as the black speckle ratio increases, the higher probability of the number of white speckles passing through the object to be imaged deviates from the statistical average, leading to a decrease in the average photocurrent received by the bucket detector and an increase in the variability of the photocurrent. This change is beneficial for improving the imaging quality with background noise.

Interferometric imaging of amplitude and phase of spatial biphoton states

High-dimensional biphoton states are promising resources for quantum applications, ranging from high-dimensional quantum communications to quantum imaging. A pivotal task is fully characterizing these states, which is generally time-consuming and not scalable when projective measurement approaches are adopted; however, new advances in coincidence imaging technologies allow for overcoming these limitations by parallelizing multiple measurements. Here we introduce biphoton digital holography, in analogy to off-axis digital holography, where coincidence imaging of the superposition of an unknown state with a reference state is used to perform quantum state tomography. We apply this approach to single photons emitted by spontaneous parametric down-conversion in a nonlinear crystal when the pump photons possess various quantum states. The proposed reconstruction technique allows for a more efficient (three orders of magnitude faster) and reliable (an average fidelity of 87%) characterization of states in arbitrary spatial modes bases, compared with previously performed experiments. Multiphoton digital holography may pave the route toward efficient and accurate computational ghost imaging and high-dimensional quantum information processing.

An Electron Computational Ghost Imaging Setup for High Resolution Imaging.

An Electron Computational Ghost Imaging Setup for High Resolution Imaging.

Optical steganography with RVNCA-based keys for 3D object

Traditional 3D image steganography is cumbersome and difficult owing to the special structure of 3D image, imposing a practical limit for its applications. Herein, we propose a 3D image steganography scheme utilizing computational ghost imaging (CGI). Furthermore, triple keys are introduced in the steganography to increase the difficulty of being cracked greatly. With the help of backward ray tracing (BRT) technology, the element image array (EIA) of the 3D object is obtained as the target of ghost imaging. For encryption, we utilize restricted vertical neighborhood cellular automata (RVNCA) to encode random masks of the CGI system as the key, which greatly improves the security of the steganography scheme and facilitates the management and transmission of the key. Finally, we reconstruct the decrypted image optically and obtain a full color and full parallax 3D image through the display device.

Resolution-independent liveness detection via computational ghost imaging

The security of liveness detection in face recognition is a crucial issue, but many attacks can spoof current face feature techniques. To enhance the security of liveness detection, a method is proposed to extract human physiological components from the object and classify the properties. The proposed method, different from traditional camera-based methods that require specific movement of the human face, separates the heart rate (HR) components from the computational ghost imaging (CGI) signal and achieves liveness detection by capturing only one image rather than image sequences. The correct rate reaches 96.0% against picture attacks and mask attacks. The average error is only 3.57% compared to commercial contact HR measuring devices. Meanwhile, this method is found resolution-independent and can work in low-resolution conditions, which is experimentally verified at a resolution of 32 × 32 pixels. This method can enhance the security of liveness detection and provide a fresh framework for physiological measurements.

Polarization-sensitive-metasurface-based microwave computational ghost imaging

Conventional multi-transmitter-based microwave computational ghost imaging (MCGI) systems have suffered from radiation source errors due to the limitation of unit performance in arrays. Radiation source errors can cause inaccuracy of the reference radiation field in MCGI, which will reduce the reconstruction quality of the target image. In this paper, a detailed error analysis of radiation sources in MCGI systems is conducted. The relationships between radiation source errors, reference radiation field and imaging results are determined. Furthermore, to mitigate the influence of radiation source error and other problems in conventional MCGI systems, such as high cost, complex design and implementation, and the interference between array elements, an improved MCGI method based on a broadband polarization-sensitive-metasurface is proposed. The metasurface in this work can modulate the incident signal and distribute the reflected signal randomly in space. Therefore, by changing the polarization angle of the radiation signal, a time-space independent signal is produced, which can achieve better detection effects in the application system. A series of simulations and experiments are performed to validate the analysis results and evaluate the proposed method’s performance. The results show that the target information can be effectively obtained by the proposed method.

BER performance of an FSOC system over atmospheric turbulence channels based on computational temporal ghost imaging.

In a free space optical communication (FSOC) system, atmospheric turbulence will increase the bit error ratio (BER) and impair FSOC link reliability. Since computational temporal ghost imaging (CTGI) has anti-interference, we present an FSOC system over atmospheric turbulence based on CTGI. The simulation results show that the BER performance of CTGI is better than on-off keying under different atmospheric turbulence regimes. To improve the performance of the CTGI scheme, the influence of the number of transmission samples and code length is analyzed. It is shown that BER performance improves with the increment of the number of samples, while code length has no impact. This scheme provides an idea for reliable communication over atmospheric turbulence and an important reference for improving wireless optical communication in an extreme environment.

An optical multiple-image authentication based on computational ghost imaging and total-variation minimization

An optical multiple-image authentication is suggested using computational ghost imaging and total-variation minimization. Differing from encrypting multiple images into a noise-like ciphertext directly, as described in most conventional authentication methods, the related encoded information is embedded into a cover image to avoid the attention of eavesdroppers. First, multiple images are encoded to form real-valued sequences composed of corresponding bucket values obtained by the aid of computational ghost imaging, and four sub-images are obtained by decomposing the cover image using wavelet transform. Second, measured sequences are embedded into one of the sub-images, and embedding positions are randomly selected using corresponding binary masks. To enhance the security level, a chaotic sequence is produced using logistic map and used to scramble measured intensities. Most importantly, original images with high quality can be directly recovered using total-variation minimization. The validity and robustness of the proposed approach are verified with optical experiments.

Improvements of Computational Ghost Imaging by Using Sequenced Speckle

This study presents a computational ghost imaging (GI) scheme that utilizes sequenced random speckle pattern illumination. The primary objective is to develop a speckle pattern/sequence that improves computational time without compromising image quality. To achieve this, we modulate the sequence of speckle sizes and design experiments based on three sequence rules for ordering the random speckle patterns. Through theoretical analysis and experimental validation, we demonstrate that our proposed scheme achieves a significantly better contrast-to-noise rate (CNR) compared to traditional GI at a similar resolution. Notably, the sequential GI method outperforms conventional approaches by providing over 10 times faster computational speed in certain speckle composition groups. Furthermore, we identify the corresponding speckle sizes that yield superior image quality, which are found to be geometrically proportional to the reference object area. This innovative approach utilizing sequenced random speckle patterns demonstrates potential suitability for imaging objects with complex or unknown shapes. The findings of this study hold great promise for advancing the field of computational GI and pseudo-thermal GI, addressing the need for improved computational efficiency while maintaining high-quality imaging.

Optical multiple-image authentication based on computational ghost imaging and hybrid non-convex second-order total variation.

An optical security method for multiple-image authentication is proposed based on computational ghost imaging and hybrid non-convex second-order total variation. Firstly, each original image to be authenticated is encoded to the sparse information using computational ghost imaging, where illumination patterns are generated based on Hadamard matrix. In the same time, the cover image is divided into four sub-images with wavelet transform. Secondly, one of sub-images with low-frequency coefficients is decomposed using singular value decomposition (SVD), and all sparse data are embedded into the diagonal matrix with the help of binary masks. To enhance the security, the generalized Arnold transform is used to scramble the modified diagonal matrix. After using SVD again, the marked cover image carrying the information of multiple original images is obtained using the inverse wavelet transform. In the authentication process, the quality of each reconstructed image can be greatly improved based on hybrid non-convex second-order total variation. Even at a very low sampling ratio (i.e., 6%), the existence of original images can be efficiently verified using the nonlinear correlation maps. To our knowledge, it is first to embed sparse data into the high-frequency sub-image using two cascaded SVDs, which can guarantee high robustness against the Gaussian filter and sharpen filter. The optical experiments demonstrate the feasibility of the proposed mechanism, which can provide an effective alternative for the multiple-image authentication.

Defogging computational ghost imaging via eliminating photon number fluctuation and a cycle generative adversarial network

Imaging through fluctuating scattering media such as fog is of challenge since it seriously degrades the image quality. We investigate how the image quality of computational ghost imaging is reduced by fluctuating fog and how to obtain a high-quality defogging ghost image. We show theoretically and experimentally that the photon number fluctuations introduced by fluctuating fog is the reason for ghost image degradation. An algorithm is proposed to process the signals collected by the computational ghost imaging device to eliminate photon number fluctuations of different measurement events. Thus, a high-quality defogging ghost image is reconstructed even though fog is evenly distributed on the optical path. A nearly 100% defogging ghost image is obtained by further using a cycle generative adversarial network to process the reconstructed defogging image.