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.
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.
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.
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.
Quantum computing has emerged as a revolutionary paradigm in numerous fields owing to its basis in quantum mechanical concepts such as quantum entanglement and parallelism. This has potential in various applications including computer vision, particularly, image processing and compression. Applications that depend on largescale image data for storing, processing, and transmission have to rely on compression methods for real-time processing. While the classical methods based on discrete cosine transformations (DCT used in JPEG) and discrete wavelet transformations (DWT) perform image compression efficiently, they suffer from trade-off between loss-less compression and compression ratios. In the current work, we would like to explore the usefulness of implementing quantum wavelet transforms for image compression for better PSNR values and execution times. We compare the application of quantum Haar wavelet transform (QHWT) with different quantum encoding methods such as NASS and FRQI and find that NASS-encoded images on application of QHWT gives better PSNR values and shorter runtime with visibly closer details to the original images, showcasing potential for efficient and faster image compression methods.
An adaptive quantum image encryption method based on wavelet transform is designed. Since the characteristic of most information is centralized in the low frequency part after performing the wavelet transform, it reserves the image low frequency information only, so as to reduce the encryption workload. Then it encrypts the low frequency information by the random key stream generated by logistic map, the encryption process is realized by implementing XOR operation. In the decryption process, it carries out zero filling operations for high frequency coefficient to recover the decryption images which are equal to the plain images. At the same time, the relevant quantum logical circuit is designed. Statistical simulation and theoretical analysis demonstrate that the proposed quantum image encryption algorithm has higher security and lower computational complexity. So it is adaptive to the scenes that need to encrypt a large number of images during network transmission.
As one of the important branches of quantum image processing, quantum image watermarking technology has been studied by many related personnel. However, most of them are performed in the time domain, and there are relatively few algorithms for quantum image watermarking in the transform domain. This paper proposes a quantum image watermarking technology based on quantum D4 wavelet transform, which specifically includes several aspects. Combining quantum wavelet transform and controlled-rotating gate, this paper proposed a quantum image watermarking algorithm for the modified flexible representation of quantum images (FRQIM) and the normal arbitrary superposition state (NASS). Firstly, the wavelet coefficients of the image are obtained by quantum wavelet transform, then the rotating gate is designed by the information of the watermark image, then the embedding position of the watermark image information is controlled by the controlled gate, and finally the watermark information is embedded in the carrier image by the controlled-rotating gate. This scheme makes full use of the parallelism of quantum computing and can operate on two images at the same time. The simulation results show that for different image combinations, the embedded image is not significantly different from the original image. Compared with the quantum image watermarking algorithm that uses the quantum Fourier transform, the image distortion after watermarking is smaller, and there are more options for embedding the image.