Ghost Imaging Algorithm Research Articles

A super-resolution algorithm of Ghost Imaging using CNN with Grouped orthonormalization algorithm Constraint

Ghost imaging (GI) is capable of reconstructing images under low-light conditions by single-pixel measurements. However, improving image resolution often requires extensive single-pixel sampling, limiting practical applications. Here we propose a super-resolution algorithm of GI using Convolutional neural network with Grouped orthonormalization algorithm Constraint (GICGC), which aims to reconstruct images at super-resolution with strong local regularities and self-similarity. The proposed algorithm, a versatile approach, has been demonstrated to outperform several other widely used GI algorithms in terms of spatial resolution and sampling rate. Our findings are supported by rigorous benchmark tests and experimental validations in challenging environments, including multimode fibers. The imaging experimental results demonstrate that GICGC achieves superior performance in reconstructing image linewidth and contrast, effectively doubling resolution capability by approximately 2.1 times, indicating significant potential in biomedical imaging and other fields. We believe this study represents a novel breakthrough in universal super-resolution ghost imaging and paves the way for its practical applications.

Cross-waveband optical computing imaging.

A novel, to the best of our knowledge, cross-spectral optical computing imaging experiment has been achieved through a single exposure of a charge-coupled device. The experimental setup integrates single-pixel imaging (SPI) with ghost imaging (GI) through a photoelectric conversion circuit and a synchronous modulation system. The experimental process involves modulation in one wavelength band (in SPI) and demodulation using the GI algorithm in another. Significantly, our approach utilizes optical computing demodulation, a departure from the conventional electronic demodulation in GI (SPI), which involves the convolution between the bucket optical signals and the modulated patterns on the digital micromirror device. A proof-of-concept cross-band imaging experiment from near-infrared to visible light has been carried out. The results highlight the system's ability to capture images at up to 20 frames per second using near-infrared illumination, which are then reconstructed in the visible light spectrum. This success not only validates the feasibility of our approach but also expands the potential applications in the SPI or GI fields, particularly in scenarios where two-dimensional detector arrays are either unavailable or prohibitively expensive in certain electromagnetic spectra such as x-ray and terahertz.

Wavelength division multiplexing visible light communication with wide incident angle enabled by perovskite quantum dots

In this paper, a wavelength division multiplexing (WDM) visible light communication (VLC) system based on the perovskite quantum dots (QDs) with two different fluorescence wavelengths is demonstrated. This system consists of a transmitter, free space channel and a receiver. The NRZ-OOK (non-return-zero on-off-keying) signals are transmitted in this channel to achieve WDM visible light communication at a transmission distance of 60 cm, with a maximum transmission capacity of 100 Mbps in the field of view of 80°. In addition, computational temporal ghost imaging (CTGI) algorithm is used to reduce the bit error rate (BER) of the received signals and improve maximum transmission angle to 120°. The proposed WDM system paves the way for visible light communication in free space.

Real-time ghost imaging algorithm on the multidimensional vector matrix Walsh transformation with spatiotemporal free-fps.

In this research, we propose a real-time spatiotemporal free-fps algorithm based on the multidimensional vector matrix Walsh transform with an adjustable ghost imaging video quality and a frame rate to address the issues of uneven imaging speed, fixed imaging frame rate, and uncomfortable appearance in real-time ghost imaging videos of moving objects. This algorithm utilizes the temporal and spatial correlation of ghost imaging videos to achieve free and adjustable video frame rates in time without being limited by DMD refresh rates. Improving the spatial information of a single frame in space enhances the smoothness of ghost imaging videos, making the appearance of ghost imaging videos more comfortable. To achieve this, a four-dimensional vector Walsh transform kernel matrix is used to transform and reconstruct the high-quality images of the target object. Then the reconstructed high-quality image is spatially interpolated to enhance spatial information. Reasonable frame rate parameters are set based on the corresponding relationship between the detection values of the adjacent frames and speckle, improving the ghost imaging video in both time and space and achieving a smooth real-time ghost imaging video with an adjustable quality and frame rate. The simulation and experimental results of moving objects show that our algorithm solves the limitation of a DMD refresh rate compared with the existing ghost imaging video methods and makes the ghost imaging video more comfortable and smoother in real time. The PSNR of the objective evaluation index is increased by 12%. Regarding a subjective evaluation, this paper proposes an adaptive parameterless evaluation algorithm (APEA) for images with different resolutions based on the NRSS, which improved the structure retention degree by 13% and the Brisque parameter evaluation by 70%. We propose an adaptive parameterless video comfort evaluation algorithm (APVCEA) to evaluate the subjective comfort of ghost imaging videos by 14% compared with traditional methods.

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.

Elimination of signal amplitude disturbance in ghost imaging using an auxiliary laser channel.

Ghost imaging can be used to detect objects in a nonstationary environment or in the presence of variable ambient light, making it attractive when conventional imaging methods are ineffective. However, the conventional ghost imaging algorithm is susceptible to temporal fluctuations in the detected signal. In this work, we propose a polarization-multiplexed auxiliary laser channel propagating along the same optical path with the main one. The signal in the auxiliary channel is used as a reference and allows the elimination of signal disturbance. A quantitative analysis and comparison of the proposed method's performance to the high-pass filtering method are demonstrated. For an illumination pattern refresh rate of 10Hz, effective suppression of bucket signal fluctuations has been experimentally demonstrated. For a disturbance frequency from 1Hz to 10Hz, the auxiliary channel method demonstrated a ghost image Pearson correlation coefficient (PCC) of not less than 0.70, while the high-pass filtering method showed a PCC sharp drop from 0.65 to 0.02.

Imaging quality improvement of ghost imaging under high correlation coefficient between speckle patterns

High correlation coefficient between speckle patterns (CCSP) results in poor imaging quality in ghost imaging (GI), especially for long-distance imaging. In this paper, we derive the analytic formula of CCSP generated by RGG and verify its effectiveness through experiments. Aiming at the degradation of imaging quality caused by high average correlation coefficient, we propose a new subset division scheme based on ordered subset expectation maximization technique to improve the quality of ghost-image. The experimental and simulation results demonstrate that our scheme can get better imaging quality under the same average correlation coefficient when compared with the commonly used GI algorithms. Even when these algorithms fail to reconstruct the target due to high average correlation coefficient, our scheme still obtains good imaging results.

Performance evaluation of plastic optical fiber communication using micro-lens coupling and computational temporal ghost imaging algorithm.

Plastic optical fiber communication (POFC) systems are particularly sensitive to signal performance and power budget. In this paper, we propose what we belive to be a novel scheme to jointly enhance the bit-error-ratio (BER) performance and coupling efficiency for multi-level pulse amplitude modulation (PAM-M) based POFC systems. The computational temporal ghost imaging (CTGI) algorithm is developed for PAM4 modulation for the first time to resist the system distortion. The simulation results reveal that enhanced BER performance and clear eye diagrams are acquired by using CTGI algorithm with an optimized modulation basis. Experimental results also investigate and show, with CTGI algorithm, the BER performance for 180 Mb/s PAM4 signals is enhanced from 2.2 × 10-2 to 8.4 × 10-4 over 10 m POF by using a 40 MHz photodetector. The POF link is equipped with micro-lenses at its end faces by using a ball-burning technique, which helps to increase the coupling efficiency from 28.64% to 70.61%. Both simulation and experimental results show that the proposed scheme is feasible to achieve a cost-effective and high-speed POFC system with short reach.

Algorithm-Dependent Computational Ghost Encryption and Imaging

We demonstrate an algorithm-dependent computational ghost imaging (GI) by proposing a pattern multiplexing method. Based on the characteristics of three typical GI algorithms (i.e., traditional second-order GI, differential GI, total variational regularization GI), we design a set of pseudorandom patterns to achieve different reconstructed images with different GI algorithms. With our designed patterns, total variational regularization GI can be used for imaging unknown scenes or prehidden images, while traditional second-order GI and differential GI are used for encrypt other different images. Not only being critical for imaging quality in GI, reconstruction algorithms in our simulations and experiments demonstrate their potential role in multiple-image reconstruction, providing an idea for the application of GI in image encryption.

Analysis of the allowable maximum amplitude of random jitter in computational ghost imaging.

The imaging blur caused by the relative motion between an imaging system and an imaging target can be eliminated by a compensation operation based on the motion law, although it is invalid when the movement is random. In this paper, the influence of the random jitter on imaging resolution is investigated quantitatively in a computational ghost imaging system, and the maximum of random-jitter amplitude that the system can allow is analyzed. The numerical and experimental results verify our conclusion, and the error between the experiment and simulation is less than 12%. The main reason for the error is the disturbance of experimental noise. By using ghost imaging algorithms to reduce the corresponding impact, this error can be further reduced to 6%.

Derivative ghost imaging

We propose a new experimentally verified ghost imaging (GI) mechanism, derivative GI. Our innovation is that we use the derivatives of the intensities of the test light and the reference light for imaging. Experimental results show that by combining derivative GI with the standard GI algorithm, multiple independent signals can be obtained in one measurement. This combination greatly reduces the number of measurements and the time required for data acquisition and imaging. Derivative GI intrinsically does not produce the storage-consuming background term of GI, so it is suitable for on-chip implementation and makes practical application of GI easier.

Classical Ghost Imaging: A Comparative Study of Algorithmic Performances for Image Reconstruction in Prospect of Plenoptic Imaging

Ghost Imaging has been extensively explored for 25 years for a two reasons: the rich physics of second-order photon correlations that enable this imaging scheme and the possibility of implementing new imaging protocols with interesting real-life applications, e.g. imaging in turbulent media, investigation of sensitive samples in low-flux regimes, 3-D plenoptic imaging, and so on. Since the first demonstration of Ghost Imaging, several extended versions of the Traditional Ghost Imaging algorithm have been proposed, such as Correspondence Ghost Imaging, Pseudo-Inverse Ghost Imaging, and normalization techniques that rely on different computational approaches to obtain the image from measured data. So far, a direct comparison of all above-mentioned protocols for the same experimental parameters is still lacking. In this work, we experimentally and numerically implement a number of different methods and systematically compare them in terms of the obtained SNR and computational cost. Furthermore, we investigate their compatibility with Correlation Plenoptic Imaging, a technique strictly connected to Ghost Imaging, that allows refocusing of images, increasing the depth of field (DOF) and making 3D visualization possible. Our results can provide useful guidelines for the choice of a suitable numerical algorithm for in the light of Ghost Imaging applications.

Influence of pulse characteristics on ghost imaging lidar system

A pulsed pseudo-thermal light source obtained using a rotating ground glass disk, spatial light modulator, or digital micromirror device is widely used in a ghost imaging (GI) lidar system. The property of the pulsed pseudothermal light field determines the reconstruction quality of the image in the GI lidar system, which depends on the pulse extinction ratio (PER) and pulse duty ratio. In this paper, pseudo-thermal light fields obtained at different pulse characteristics are given, taking into account the influence of the exposure time of the charge-coupled device (CCD) camera. The statistical distribution, contrast, and normalized intensity correlated function of the pseudo-thermal light field at different pulse characteristics are analyzed quantitatively for what we believe is the first time. Then the peak signal-to-noise ratio of the reconstructed image using a GI algorithm and a differential ghost imaging (DGI) algorithm is numerically simulated. The simulation results demonstrate that the PSNR decreases as the PER decreases, which is affected by the pulse duty ratio and the CCD exposure time. The deterioration of the reconstruction quality can be reduced by using a DGI algorithm or by shorting the exposure time of the CCD in the GI lidar system.

Digital filtering ghost imaging to remove light disturbances.

Ghost imaging (GI) can reconstruct the image of an object when the light traveling from the object to the detector is scattered or distorted. It is usually used in complicated environments, where the environmental light may heavily impact measurement. However, the traditional GI algorithm will be seriously affected if the environmental light changes during the measurement. In this paper, we analyze the frequency of environmental light and the light source, and introduce a digital filtering method that can improve the image quality of the traditional GI algorithm. Compared to the traditional GI algorithm, the digital filtering method can obtain an image even if the environmental light changes seriously.

Signal transmission of 4 GHz beyond the system bandwidth in UV-C LED communication based on temporal ghost imaging

Due to the bandwidth limitation of the ultraviolet-C (UV-C) optical communication system and strong channel attenuation, it is difficult to transmit high-frequency signals. In this paper, the temporal ghost imaging (TGI) algorithm was first applied to the UV-C communication experimentally, and we realized the transmission of a 4 GHz signal through 95.34 MHz system bandwidth. The study indicates that the TGI algorithm can significantly improve the signal-to-noise ratio (SNR) compared with the on–off keying method. Our research provides a new approach for alleviating transmission frequency limitation due to poor SNR and insufficient hardware bandwidth.

Non-imaging target recognition algorithm based on projection matrix and image Euclidean distance by computational ghost imaging

With the development of target recognition technology, people pay more and more attention to target recognition. This paper proposed a non-imaging target recognition technology based on projection matrix and image Euclidean distance by computational ghost imaging. The main features of spatial sample images are extracted by principal component analysis. The projection matrix of eigenspace is used as the modulation matrix in computational ghost imaging algorithm to reduce data redundancy. And by calculating the image Euclidean distance, the correlation of pixels is taken into full consideration in spatial position, so as to improve the accuracy of traditional target recognition algorithms. In this paper, the target recognition is realized by directly using the detector observations of the computational ghost imaging system based on the eigenspace projection matrix and the calculation of the image Euclidean distance. The algorithm not only has better recognition performance without reconstructing the image.

Information transmission based on a Fourier transform and ascending coding temporal ghost imaging algorithm

In this paper, based on the specific analysis of a temporal ghost imaging (TGI) algorithm, image coding transmission is realized by combining the compression characteristics of a Fourier transform, the convenient control and management function of ascending coding (AC) and the precise transmission function of TGI. AC, as a kind of sorting coding, has the characteristics of fast speed, high precision and wide application range. This paper analyzes noise attack, information, bit error rate (BER) and similarity, etc. Verified by simulation experiment, this algorithm can improve the compressibility of the encoded image, improve the difficulty of decoding by an attacker, reduce the BER in the process of image coding transmission, enhance the ability of anti-interference, realize accurate image coding transmission and solve the problems of low accuracy and low security of image transmission reconstruction at present.

Influence of Atmospheric Turbulence Channel on a Super-Resolution Ghost Imaging Transmission System Based on Plasmonic Structure Illumination Microscopy

Ghost imaging is a research focus of image area with various advantages against traditional imagings. However, most of the existing works didn’t have a better resolution than the diffraction limit. In this work, we presented a ghost imaging system with plasmonic structure illumination microscopy (PSIM), to achieve super-resolution imaging. The resolution can reach 3 to 4 times of diffraction limit with surface plasmon polaritons (SPPs) and structure illumination microscopy (SIM) theory. In addition, imaging results are obtained accordingly. This method has great research value in medical fields such as micro-imaging and endoscope. Then, we used the gamma-gamma intensity-fluctuation model to simulate the ghost imaging system in atmospheric turbulence channel. By setting proper values of the parameters such as transmission distance and refractive-index structure parameter, the peak signal-to-noise ratio (PSNR) performance and symbol-error rate (SER) performance are obtained to evaluate the imaging quality, which provides a theoretical model to further research the ghost-imaging algorithm.

Imaging reconstruction comparison of different ghost imaging algorithms

As an indirect and computational imaging approach, imaging reconstruction efficiency is critical for ghost imaging (GI). Here, we compare different GI algorithms, including logarithmic GI and exponential GI we proposed, by numerically analysing their imaging reconstruction efficiency and error tolerance. Simulation results show that compressive GI algorithm has the highest reconstruction efficiency due to its global optimization property. Error tolerance studies further manifest that compressive GI and exponential GI are sensitive to the error ratio. By replacing the bucket input of compressive GI with different bucket object signal functions, we integrate compressive GI with other GI algorithms and discuss their imaging efficiency. With the combination between the differential GI (or normalized GI) and compressive GI, both reconstruction efficiency and error tolerance will present the best performance. Moreover, an optical encryption is proposed by combining logarithmic GI, exponential GI and compressive GI, which can enhance the encryption security based on GI principle.

Ghost imaging enhancement for detections of the low-transmittance objects

The underwater environment is extremely complex and variable, which makes it difficult for underwater robots detecting or recognizing surroundings using images acquired with cameras. Ghost imaging as a new imaging technique has attracted much attention due to its special physical properties and potential for imaging of objects in optically harsh or noisy environments. In this work, we experimentally study three categories of image reconstruction methods of ghost imaging for objects of different transmittance. For high-transmittance objects, the differential ghost imaging is more efficient than traditional ghost imaging. However, for low-transmittance objects, the reconstructed images using traditional ghost imaging and differential ghost imaging algorithms are both exceedingly blurred and cannot be improved by increasing the number of measurements. A compressive sensing method named augmented Lagrangian and alternating direction algorithm (TVAL3) is proposed to reduce the background noise imposed by the low-transmittance. Experimental results show that compressive ghost imaging can dramatically subtract the background noise and enhance the contrast of the image. The relationship between the quality of the reconstructed image and the complexity of object itself is also discussed.