arXiv subjects

Wen-Kai Yu

Publications and source records attributed to Wen-Kai Yu.

At least 19 recordsLinked to original sources

arXiv2026

Spatial nonlocality imaging via metasurface

Bell nonlocality is both a defining signature of entanglement and a key quantum information resource. However, visualizing and certifying nonlocal correlations across a spatially multimode photonic field remains challenging due to the rapidly growing measurement cost of spatially resolved projective tests. To address this issue, we build a spatial nonlocality imaging scheme that directly reveals the spatial distribution of quantum nonlocality by integrating a metasurface that performs parallel polarization projections with a quantum-adaptive neural network. Spatially resolved Clauser--Horne--Shimony--Holt (CHSH) tests are realized over a 400-pixel biphoton field using an average of only 1.7 detected coincidence pairs per pixel per basis. This approach yields a nonlocality image that maps the two-dimensional spatial distribution of Bell violations across the optical field and reveals the target-state-dependent spatial evolution of Bell violations. It provides a highly resource-efficient route to large-scale Bell certification and opens new possibilities for exploiting spatially multimode entanglement in quantum imaging, quantum networking, and scalable photonic quantum technologies.

quant-ph↗

arXiv2023

Physics-driven generative adversarial networks empower single-pixel infrared hyperspectral imaging

A physics-driven generative adversarial network (GAN) was established here for single-pixel hyperspectral imaging (HSI) in the infrared spectrum, to eliminate the extensive data training work required by traditional data-driven model. Within the GAN framework, the physical process of single-pixel imaging (SPI) was integrated into the generator, and the actual and estimated one-dimensional (1D) bucket signals were employed as constraints in the objective function to update the network's parameters and optimize the generator with the assistance of the discriminator. In comparison to single-pixel infrared HSI methods based on compressed sensing and physics-driven convolution neural networks, our physics-driven GAN-based single-pixel infrared HSI can achieve higher imaging performance but with fewer measurements. We believe that this physics-driven GAN will promote practical applications of computational imaging, especially various SPI-based techniques.

eess.IV↗

arXiv2022

Secondary complementary balancing compressive imaging with a free-space balanced amplified photodetector

Single-pixel imaging (SPI) has attracted widespread attention because it generally uses a non-pixelated photodetector and a digital micromirror device (DMD) to acquire the object image. Since the modulated patterns seen from two reflection directions of the DMD are naturally complementary, one can apply complementary balanced measurements to greatly improve the measurement signal-to-noise ratio and reconstruction quality. However, the balance between two reflection arms significantly determines the quality of differential measurements. In this work, we propose and demonstrate a simple secondary complementary balancing mechanism to minimize the impact of the imbalance on the imaging system. In our SPI setup, we used a silicon free-space balanced amplified photodetector with 5 mm active diameter which could directly output the difference between two optical input signals in two reflection arms. Both simulation and experimental results have demonstrated that the use of secondary complementary balancing can result in a better cancellation of direct current components of measurements and a better image restoration quality.

physics.optics↗

arXiv2022

Single-pixel imaging based on weight sort of the Hadamard basis

Single-pixel imaging (SPI) is very popular in subsampling applications, but the random measurement matrices it typically uses will lead to measurement blindness as well as difficulties in calculation and storage, and will also limit the further reduction in sampling rate. The deterministic Hadamard basis has become an alternative choice due to its orthogonality and structural characteristics. There is evidence that sorting the Hadamard basis is beneficial to further reduce the sampling rate, thus many orderings have emerged, but their relations remain unclear and lack a unified theory. Given this, here we specially propose a concept named selection history, which can record the Hadamard spatial folding process, and build a model based on it to reveal the formation mechanisms of different orderings and to deduce the mutual conversion relationship among them. Then, a weight ordering of the Hadamard basis is proposed. Both numerical simulation and experimental results have demonstrated that with this weight sort technique, the sampling rate, reconstruction time and matrix memory consumption are greatly reduced in comparison to traditional sorting methods. Therefore, we believe that this method may pave the way for real-time single-pixel imaging.

eess.IV↗

arXiv2020

Fragment-synthesis-based multiparty cryptographic key distribution over a public network

A secure optical communication requires both high transmission efficiency and high authentication performance, while existing cryptographic key distribution protocols based on ghost imaging have many shortcomings. Here, based on computational ghost imaging, we propose an interactive protocol that enables multi-party cryptographic key distribution over a public network and self-authentication by setting an intermediary that shares partial roles of the server. This fragment-synthesis-based authentication method may facilitate the remote distribution of cryptographic keys.

eess.IV↗

arXiv2020

Multi-wavelet residual dense convolutional neural network for image denoising

Networks with large receptive field (RF) have shown advanced fitting ability in recent years. In this work, we utilize the short-term residual learning method to improve the performance and robustness of networks for image denoising tasks. Here, we choose a multi-wavelet convolutional neural network (MWCNN), one of the state-of-art networks with large RF, as the backbone, and insert residual dense blocks (RDBs) in its each layer. We call this scheme multi-wavelet residual dense convolutional neural network (MWRDCNN). Compared with other RDB-based networks, it can extract more features of the object from adjacent layers, preserve the large RF, and boost the computing efficiency. Meanwhile, this approach also provides a possibility of absorbing advantages of multiple architectures in a single network without conflicts. The performance of the proposed method has been demonstrated in extensive experiments with a comparison with existing techniques.

eess.IV↗

arXiv2019

Unified probability explanation for ghost imaging with thermal light

Ghost imaging (GI) is an intriguing imaging technology which achieves the object images through intensity correlation between reference patterns and bucket signal. Here, we propose a probability model to explain the imaging mechanism of this modality, by assuming that the reference patterns fulfill an arbitrary identical distribution and that the objects are of gray-scale. We have proven that the probability of the reconstructed pixel values in the pixel region of the same original gray value obeys a Gaussian distribution, no matter which functional form of the reference patterns is used in correlation calculation. Both simulation and experiments have demonstrated that the probability of recovered pixel values are highly consistent with their Gaussian theoretical distribution, while their variance explains the appearance of reconstruction noise. In addition, we have also extend this theory to other classic correlation functions, e.g., normalized GI and differential GI. The results have shown that there is a linear relationship between reconstruction means in specified pixel regions and original gray values, which might provide a unified explanation for GI with thermal light.

eess.IV↗

arXiv2019

Phase retrieval without prior knowledge via single-shot Fraunhofer diffraction pattern of complex object

Fraunhofer diffraction is a well-known phenomenon achieved with most wavelength even without lens. A single-shot intensity measurement of diffraction is generally considered inadequate to reconstruct the original light field, because the lost phase part is indispensable for reverse transformation. Phase retrieval is usually conducted in two means: priori knowledge or multiple different measurements. However, priori knowledge works for certain type of object while multiple measurements are difficult for short wavelength. Here, by introducing non-orthogonal measurement via high density sampling scheme, we demonstrate that one single-shot Fraunhofer diffraction pattern of complex object is sufficient for phase retrieval. Both simulation and experimental results have demonstrated the feasibility of our scheme. Reconstruction of complex object reveals depth information or refraction index; and single-shot measurement can be achieved under most scenario. Their combination will broaden the application field of coherent diffraction imaging.

eess.IV↗

arXiv2019

Formation mechanism of correspondence imaging with thermal light

Correspondence imaging can achieve positive-negative ghost images by just conditional averaging of partial patterns, without treating bucket intensities as weights. To explain its imaging mechanism, we develop a probability theory assuming the targets are of gray-scale and the thermal reference speckles obey an arbitrary independent and identical distribution. By both simulation and experiments, we find that the recovered values in each region of the same original gray value conditionally obey a Gaussian distribution. A crosspoint-to-standard-deviation ratio is used as the figure of merit to prove that the patterns with respect to larger bucket values generate a positive image with a higher quality, vice versa for negative one. This work complements the theory of ghost imaging.

physics.optics↗

arXiv2019

Domino successive-deviation ghost imaging

Traditional ghost imaging acquires images via the correlation of the intensity fluctuations of reference patterns and bucket values, and can even generate positive-negative images by conditionally averaging partial patterns. Here, we propose a domino successive-deviation ghost imaging method, which owns a good image quality comparable to that of differential ghost imaging with real-time fast computation, and a better robustness in practical scenarios where measurement noise and the instability of illuminating source coexists. Furthermore, it happens to generate real-time positive and negative images, giving a new insight into physical essence of positive-negative ghost image phenomenon. Both simulation and experimental results have demonstrated the feasibility of our approach. Therefore, this work complements the theory of ghost imaging and opens a door to practical applications of real-time single-pixel imaging.

eess.IV↗

arXiv2019

Three-dimensional imaging with single-frame jigsaw-puzzle-reorganized sinusoidal fringe using multi-pixel axial flat brush scanning

Structured-light three-dimensional (3D) imaging can achieve 3D shape of a stationary object via one or more pixelated array cameras with phase-shifting illumination. In order to extend 3D imaging to moving scenarios, we propose a 3D imaging method with double projection of a single-frame modulated light pattern and a sampling pattern. It can continuously image the moving 3D scene by making multi-pixel detector axial flat brush scan along the motion axis. Utilizing spatial multiplexing for multiple single-pixel imaging, each single-pixel does not need to keep staring at some part of the object, avoiding motion blur problem. The performance of our method has been demonstrated by numerical simulations. Given this, we believe that the technique paves the way to practical applications including product line 3D monitoring.

eess.IV↗

arXiv2019

Cryptographic key distribution over a public network via variance-based watermarking in compressive measurements

The optical communication has an increasing need for security in public transmission scenarios. Here we present a protocol for cryptographic key distribution over a public network via photon-counting compressive imaging system with watermarking, which utilizes watermarking technique to distribute secure keys, and uses reconstructed images for simultaneous identity authentication and tampering identification. The watermark is embedded in the rearranged compressed measurements of the object, and then the signal is transmitted through a public network. At the receiving terminal, the legitimate users can easily extract the watermark as the cryptographic key by using initial keys and the variance characteristic of random measurements. Artificial tampering and attacks can be detected by the accurately retrieved images. The realization of this protocol is a step forward toward the practical applications, and will be beneficial for the broader fields of optical security in many ways.

cs.CR↗

arXiv2019

Super sub-Nyquist single-pixel imaging by means of cake-cutting Hadamard basis sort

Single-pixel imaging via compressed sensing can reconstruct high-quality images from a few linear random measurements of an object/scene known a priori to be sparse or compressive, by using a point/bucket detector without spatial resolution. Nevertheless, it still faces a harsh trade-off among the acquisition time, the spatial resolution and the signal-to-noise ratio. Here we present a new compressive imaging approach with use of a strategy called cake-cutting which optimally reorders the deterministic Hadamard basis. By this means, the number of measurements can be dramatically reduced by more than two orders of magnitude. Furthermore, by exploiting the structured characteristic of the Hadamard matrix, we can accelerate the computational process and simultaneously reduce the memory consumption of storing the matrix. The proposed method is capable of recovering an image of the object, of pixel size $1024\times1024$, with a sampling ratio of even 0.2%, thereby realizing super sub-Nyquist sampling and significantly reducing the acquisition time. Moreover, through the differential modulation/measurements, we demonstrate this method with a single-photon single-pixel camera under low light condition and retrieve clear images through partially obscuring scenes. This described practical method complements the single-pixel imaging approaches and can be applied to a variety of fields, such as video, night vision goggles and automatic drive.

eess.IV↗

arXiv2019

Single-pixel imaging with origami pattern construction

Single-pixel compressive imaging can recover images from a small amount of measurements, offering many benefits especially for the scenes where the array detection is unavailable. However, the widely used random patterns fail to explore internal relations between the patterns and the image reconstruction. Here we propose a single-pixel imaging method based on origami pattern construction with a better imaging quality, but with less uncertainty of the pattern sequence. It can decrease the sampling ratio even to 0.5\%, really realizing super sub-Nyquist sampling. The experimental realization of this approach is a big step forward toward the real-time compressive video applications.

eess.IV↗

arXiv2017

Compressive fluorescence spectral imaging with a spectrometer

We present an efficient approach and principle experiment for compressive sensing (CS) fluorescence spectral imaging. According to the dimension-reduced effect of CS, the spectral and spatial information was simultaneously obtained by using a fiber spectrometer without mechanical scanning. As a method verification, we demonstrated spectral imaging under only two typical wavelengths, but the spectral resolution is up to 1.4nm depended on the fiber spectrometer. The method could obtain 50% light energy from the object, much larger compared with mechanical scanning which detects light of only one point per measurement. The relationship between sampling rate and image quality is also discussed in this study.

physics.ins-det↗

arXiv2016

Efficient phase retrieval based on dark fringe recognition with an ability of bypassing invalid fringes

This paper discusses the noisy phase retrieval problem: recovering a complex image signal with independent noise from quadratic measurements. Inspired by the dark fringes shown in the measured images of the array detector, a novel phase retrieval approach is proposed and demonstrated both theoretically and experimentally to recognize the dark fringes and bypass the invalid fringes. A more accurate relative phase ratio between arbitrary two pixels is achieved by calculating the multiplicative ratios (or the sum of phase difference) on the path between them. Then the object phase image can be reconstructed precisely. Our approach is a good choice for retrieving high-quality phase images from noisy signals and has many potential applications in the fields such as X-ray crystallography, diffractive imaging, and so on.

cs.CV↗

arXiv2015

Spectral imaging with dual compressed sensing

We experimentally demonstrated a spectral imaging scheme with dual compressed sensing. With the dimensions of spectral and spatial information both compressed, the spectral image of a colored object can be obtained with only a single point detector. The effect of spatial and spectral modulation numbers on the imaging quality is also analyzed. Our scheme provides a stable, highly consistent approach of spectral imaging.

physics.optics↗

arXiv2015

Single-pixel ghost microscopy based on compressed sensing and complementary modulation

An experiment demonstrating single-pixel single-arm complementary compressive microscopic ghost imaging based on a digital micromirror device (DMD) has been performed. To solve the difficulty of projecting speckles or modulated light patterns onto tiny biological objects, we instead focus the microscopic image onto the DMD. With this system, we have successfully obtained a magnified image of micron-sized objects illuminated by the microscope's own incandescent lamp. The image quality of our scheme is more than an order of magnitude better than that obtained by conventional compressed sensing with the same total sampling rate, and moreover, the system is robust against intensity instabilities of the light source and may be used under very weak light conditions. Since only one reflection direction of the DMD is used, the other reflection arm is left open for future infrared light sampling. This represents a big step forward toward the practical application of compressive microscopic ghost imaging in the biological and material science fields.

physics.optics↗