In order to reduce the time overhead of quantum imaging, a new ranging-assisted quantum imaging method based on coincidence counting is proposed in this paper. Firstly, the Digital Micromirror Device (DMD) is used to select the ranging area in the imaging area, and photon arrival time sequences on signal and reference light paths are recorded by delay coincidence. Secondly, the second-order correlation curve is drawn according to the coincidence count values to obtain the delay difference of these two optical paths. This delay difference corrects the photon arrival time sequences corresponding to the imaging area. Finally, the coincidence counting is performed based on the corrected time sequences, and the quantum imaging result is obtained according to the coincidence count values. Experimental results show that the proposed method can greatly reduce the time overhead of quantum imaging.
In order to reduce the time overhead of quantum imaging, a new ranging-assisted quantum imaging method based on coincidence counting is proposed in this paper. Firstly, the Digital Micromirror Device (DMD) is used to select the ranging area in the imaging area, and photon arrival time sequences on signal and reference light paths are recorded by delay coincidence. Secondly, the second-order correlation curve is drawn according to the coincidence count values to obtain the delay difference of these two optical paths. This delay difference corrects the photon arrival time sequences corresponding to the imaging area. Finally, the coincidence counting is performed based on the corrected time sequences, and the quantum imaging result is obtained according to the coincidence count values. Experimental results show that the proposed method can greatly reduce the time overhead of quantum imaging.
In recent years, quantum information technology, as a subversive and strategic technology that has attracted much attention, acquires, transmits, and processes information by means of unique physical phenomena such as quantum entanglement, nonlocality, and non-cloning. Quantum imaging technology achieves non-local imaging of targets by extracting entangled light quantum information with temporal and spatial correlation characteristics. By using the anti-interference and anti-turbulence characteristics of quantum entangled states, quantum imaging technology can break through the physical limits of traditional imaging fields, thereby improving imaging resolution and sensitivity. The latest technological development in quantum imaging has prompted researchers to study high-resolution and fast quantum imaging based on the spatial correlation characteristics of entangled photon pairs. In this circumstance, we propose a novel quantum imaging method based on two-step adaptive sampling optimization and carry out experimental verification. In concrete terms, in order to solve the problem that the efficiency of entangled light quantum imaging is limited by Digital Micromirror Device (DMD) sampling, we select the two-step adaptive sampling optimization algorithm to reduce the influence of DMD scanning on imaging efficiency. At the same time, for the sake of solving the problem that the quality of entangled photon quantum imaging is limited by the accuracy of coincidence counting, we add delay difference calculation in the imaging process and correct the signal photon arrival time pulse sequence to ensure the accuracy of coincidence counting. Finally, we conduct a large number of experiments to evaluate the performance of the two-step adaptive sampling optimization algorithm and verify the superiority of the proposed entangled quantum imaging method practically.
In the process of quantum correlation imaging, the use of a fixed sampling mode will affect the imaging efficiency and image reconstruction quality of quantum correlation imaging, and different sampling matrices will have different effects on the imaging results. Aiming at the above problems, this paper proposes an adaptive compressed imaging method based on quantum correlation (ACI). The Digtial Micromirror Devices (DMD) specific sampling mode is designed by distinguishing the different texture details of the image, and the reference light is compressed and sampled by different sampling matrices. Finally, the reference light and the signal light are matched and counted and brought into the reconstruction algorithm to obtain the target image. The experimental results show that the method effectively shortens the imaging time and improves the imaging quality. At the same time, the Toeplitz matrix in the sampling matrix has the best effect. Therefore, this method can make good use of image texture features to improve the quality of quantum correlation imaging while reducing imaging time.
To improve the quality of quantum imaging, this paper proposes a coincidence count filtering method based on integrated Gaussian filtering and wavelet transform for quantum imaging. Firstly, the photon information is collected to obtain coincident count values, and then Gaussian filtering is applied to smooth coincident count values. Secondly, discrete wavelet transform is performed on coincident count values to obtain wavelet coefficients, and Gaussian filtering is conducted on high-frequency coefficients. Finally, inverse wavelet transform is used to obtain the optimized coincidence count result, and then the target is imaged by linear mapping. Both simulation and actual tests verify that the proposed method can achieve high-quality imaging.
Three-dimensional (3D) imaging in low-light environments has broad application prospects. High-quality 3D imaging requires obtaining both the depth and reflectivity information of the target. With the rapid development of Quantum Information Technology (QIT), Quantum Imaging (QI) provides a new approach to achieve high-quality 3D imaging. However, traditional QI methods are limited to Two-dimensional (2D) imaging and cannot accurately extract the depth information from the target. These methods also suffer from insufficient precision in reflectivity calculations. Therefore, we introduce a novel quantum 3D imaging and reflectivity estimation method based on entangled photons. Specifically, we first utilize the spatiotemporal correlation characteristics of entangled photon pairs combined with coincidence measurement technology to accurately determine target depth. Second, we analyze the distribution of entangled photon numbers during free-space transmission to construct a photon-based detection probability model. Third, we use this model to derive the probability density function of coincidence counts. Finally, we estimate the surface reflectivity information through statistical analysis of coincidence counting. Experimental results demonstrate that the proposed method can accurately reconstruct both depth and reflectivity profiles of the target in low-light environments. These findings validate the effectiveness of our method and highlight the potential of quantum 3D imaging for target detection in low-light environments.
Aiming at the problem that the dynamic change of the scattering environment affects the propagation distance estimation performance by different light sources, resulting in low positioning accuracy and poor robustness, a light quantum positioning method based on integrated coincidence counting and adaptive light source selection is proposed. Specifically, the method considers the dynamic changes of the scattering environment to group the entangled light time pulse sequences, calculates the signal propagation distance of each light source under each group based on the coincidence count, and takes the relative error of each light source under each group as the basis to dynamically select different light sources for positioning. The experimental results show that the proposed method has higher positioning accuracy and stronger positioning robustness.
ABSTRACT Quantum imaging leverages the intrinsic sharpness of quantum correlations between entangled photon pairs, offering the potential for high spatial resolution and enhanced signal‐to‐noise performance. However, practical quantum imaging systems often suffer from complex optical architectures and long acquisition times, limiting their applicability in dynamic scenarios. In this work, we propose quantum Gabor holography (QGH) and introduce array‐based coincidence counting with joint probability analysis to directly extract the spatial correlations of entangled photon pairs. The system selectively identifies true photon‐pair events while effectively suppressing uncorrelated background photons and detector noise. Experiments confirm that correlation‐based QGH preserves intrinsic quantum spatial information, improves noise robustness, and enables reliable amplitude and phase reconstruction even under ultra‐weak photon flux. The proposed method provides an efficient and physically grounded pathway toward lensless, low‐light, and high‐resolution quantum imaging.