Article
Computer Science, Artificial Intelligence
Yonghua Zhang, Xiaojie Guo, Jiayi Ma, Wei Liu, Jiawan Zhang
Summary: Images captured under low-light conditions often suffer from poor visibility due to multiple degradation factors. This study proposes a network based on Retinex theory, decomposing images into illumination and reflectance components to enhance image quality. Extensive experiments show the effectiveness and superiority of this method, especially in terms of flexibility and robustness against visual defects.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2021)
Article
Engineering, Electrical & Electronic
Xianglang Wang, Youfang Lin, Shuo Zhang
Summary: We propose a multiple stream progressive restoration network to enhance and denoise light fields (LFs) under low light conditions. Three types of input are designed to fully utilize the supplementary information and preserve the epipolar information. A multi-stream interaction module is developed to aggregate features from different restoration streams. Multiple stages restoration is introduced to gradually reconstruct the LF.
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
(2023)
Article
Optics
Ashan Ariyawansa, Edward J. Figueroa, Thomas G. Brown
Summary: This method selects photon orbital angular momentum at very low light levels using spatial interference. By using Fourier phase recovery techniques, a quantum-limited Q distribution can be obtained experimentally, distinguishing states of different orbital angular momentum with high fidelity for small numbers of counts per frame. The noise equivalent photoelectron count for this measurement is 10 to the power of -5 counts per pixel per frame.
Article
Computer Science, Artificial Intelligence
Fei Zhou, Xin Sun, Junyu Dong, Xiao Xiang Zhu
Summary: This paper presents a novel SurroundNet approach that achieves very competitive performance with less than 150K parameters, which is a significant reduction in size compared to other methods. The proposed method, consisting of Adaptive Retinex Blocks and an illumination estimation function called Adaptive Surround Function, is evaluated on two real-world low-light datasets and outperforms existing methods in both performance and network parameters.
PATTERN RECOGNITION
(2023)
Article
Automation & Control Systems
Jin Chen, Yong Wang, Yujuan Han
Summary: This study proposes a Semi-Supervised Network Framework (SSNF) to enhance low-light images, decoupling the enhancement task into two stages using information entropy, Retinex, U-Net, and residual networks. Experimental results show that SSNF outperforms other advanced methods in visual effects and performance metrics.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Physics, Fluids & Plasmas
Francesco Buscemi, Valerio Scarani
Summary: The reverse process in the studies of irreversibility in statistical mechanics arises naturally from Bayesian retrodiction, providing a broader scope for fluctuation relations. Previous paradigmatic results, such as Jarzynski's equality, Crooks' fluctuation theorem, and Tasaki's two-measurement fluctuation theorem, are consistent with retrodictive arguments. Various corrections introduced to deal with nonequilibrium steady states or open quantum systems are justified as remnants of Bayesian retrodiction.
Article
Computer Science, Artificial Intelligence
Hua Zou, Xiao Lin, Huanhuan Wu, Yeh-Cheng Chen
Summary: In this paper, a predictive intelligence approach of a multi-task framework is proposed to enhance low-light images. The framework consists of coarse recovery sub-networks and cross refinement sub-networks. Experimental results demonstrate that the proposed method achieves significant improvements in various metrics compared to state-of-the-art alternatives.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Xiaojie Guo, Qiming Hu
Summary: This paper presents a novel framework for addressing the complex degradation issues of images captured in low-light environments. By decomposing the image into texture and color components, and performing noise removal, color correction, and light adjustment, the framework achieves satisfactory lighting, cleanliness, and realism.
INTERNATIONAL JOURNAL OF COMPUTER VISION
(2023)
Article
Computer Science, Artificial Intelligence
Marco Cotogni, Claudio Cusano
Summary: In this paper, we propose TreEnhance, an automatic method for enhancing low-light images. The method combines tree search theory with deep reinforcement learning to generate an enhanced version of the input image and the sequence of editing operations used. The method achieves good results in both qualitative and quantitative evaluations.
PATTERN RECOGNITION
(2023)
Article
Engineering, Electrical & Electronic
Guo-Dong Fan, Bi Fan, Min Gan, Guang-Yong Chen, C. L. Philip Chen
Summary: This study introduces an end-to-end low-light image enhancement model, MLLEN-IC, which utilizes SE-Res2block to extract deep multiscale features and incorporates illumination constraints to prevent overexposure and color unsaturation, achieving better generalization ability and stability performance.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Review
Engineering, Electrical & Electronic
Muhammad Tahir Rasheed, Daming Shi, Hufsa Khan
Summary: Low-light image enhancement is a challenging problem, and various methods have been designed to address it. This paper examines the generalization ability of these methods through experiments and proposes a large-scale image quality assessment dataset. The inconsistency of low-light evaluation methods is also studied, and suggestions for future work are provided.
Article
Engineering, Electrical & Electronic
Kai Xu, Huaian Chen, Chunmei Xu, Yi Jin, Changan Zhu
Summary: This work proposes a structure-texture aware network (STANet) for improving the perceptual quality of low-light images by exploiting the structure and texture features. The image is decomposed into structure and texture components using a fine-scale contour map guided filter, and structure-attention and texture-attention subnetworks are designed to fully exploit the characteristics of these components. A fusion subnetwork with attention mechanisms is utilized to explore the internal correlations among the global and local features.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Automation & Control Systems
Yuezhou Li, Yuzhen Niu, Rui Xu, Yuzhong Chen
Summary: This study proposes a zero-referenced adaptive filter network (ZAFN) to address the challenges in low-light image enhancement. The ZAFN model generates adaptive filters by integrating high-level contents from multiple partial scenes and conducts an iterative enlightening process using dynamically modulated low-level features. Our ZAFN model outperforms other state-of-the-art zero-referenced methods on four popular datasets.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Lingyu Zhu, Wenhan Yang, Baoliang Chen, Fangbo Lu, Shiqi Wang
Summary: Images captured in low-light conditions often suffer from visual quality degradations such as low visibility, degraded contrast, and increased noise. In this study, we propose a new method that uses a learnable guidance map from signal and deep priors to adaptively enhance low-light images in different regions. By incorporating a multi-scale dilated context collaboration, the enhancement capability of the learnable guidance map is further improved, resulting in more realistic and visually pleasing textures.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2022)
Article
Computer Science, Information Systems
Xiaozhou Lei, Zixiang Fei, Wenju Zhou, Huiyu Zhou, Minrui Fei
Summary: Low light conditions can significantly degrade image quality and cause visual task failures. Existing image enhancement technologies often suffer from overenhancement, color distortion, and high time consumption, with limited adaptability. In this study, a novel method for enhancing the lightness of low-light images is proposed. The method utilizes an energy model based on membrane vibrations induced by photon stimulations, combined with a gamma correction model. A local fusion strategy is also employed to optimize the local details of the enhanced images. Experimental results demonstrate the superiority of the proposed algorithm in terms of avoiding color distortion, restoring dark areas textures, reproducing natural colors, and reducing time cost.
IEEE TRANSACTIONS ON MULTIMEDIA
(2023)
Article
Optics
Hao Yang, Wojciech Roga, Jonathan D. Pritchard, John Jeffers
Summary: The study shows that quantum illumination has advantages over coherent states in object detection, even for simple direct photodetection. This advantage persists even when signal energy and object reflectivity are low, and background thermal noise is high. Furthermore, the advantage becomes even greater if signal beam detection probabilities are matched rather than mean photon numbers.
Article
Physics, Multidisciplinary
Stephen M. Barnett, Fiona C. Speirits, Mohamed Babiker
Summary: In summary, this paradox questions how a Gaussian beam, which has zero orbital angular momentum, can drive a quadrupole transition that requires the transfer of angular momentum to an absorbing atom.
JOURNAL OF PHYSICS A-MATHEMATICAL AND THEORETICAL
(2022)
Article
Physics, Multidisciplinary
Franziska Strasser, Stephen M. Barnett, Monika Ritsch-Marte, Gregor Thalhammer
Summary: We propose a method to measure the optical torque applied to particles of arbitrary shape using the change of angular momentum of light. The method allows for the determination of all torque components from a single interference pattern and the retrieval of the required phase using an iterative algorithm. This method provides access to the torque pertaining to individual particles as well as separate spin or orbital parts of the total torque.
PHYSICAL REVIEW LETTERS
(2022)
Article
Physics, Multidisciplinary
Stephen M. Barnett
Summary: Single-photon interference experiments appear to behave similarly to classical experiments using laser-generated fields, despite their complexity. This observation is well-known to those familiar with the topic but may be mysterious to others. We discuss the reasons behind this similarity and the limitations of this simple idea.
Article
Physics, Applied
Hao Yang, Nigam Samantaray, John Jeffers
Summary: In this article, we describe a quantum illumination scheme based on nonsimultaneous and nonoptimal measurements, and demonstrate the advantage of using multiclick measurements to reveal the presence of a target object earlier under lossy conditions.
PHYSICAL REVIEW APPLIED
(2022)
Article
Physics, Multidisciplinary
Stephen M. Barnett, Bryan J. Dalton
Summary: The Glauber-Sudarshan P-representation is widely used in quantum optics for analyzing photon statistics, while its fermionic counterpart introduced by Cahill and Glauber is less well-known. In this study, we derive both bosonic and fermionic distributions and demonstrate the relationship between the two distinct fermionic forms. We consider both single mode and multiparticle systems, obtaining expressions for moments involving mode annihilation and creation operators. Although we focus on a single type of boson or fermion for simplicity, generalization to more types is straightforward.
Article
Multidisciplinary Sciences
Christopher L. Morrison, Roberto G. Pousa, Francesco Graffitti, Zhe Xian Koong, Peter Barrow, Nick G. Stoltz, Dirk Bouwmeester, John Jeffers, Daniel K. L. Oi, Brian D. Gerardot, Alessandro Fedrizzi
Summary: This paper presents a scheme for quantum key distribution using solid-state single-photon emitters. By frequency converting single photons generated by quantum dots to 1550 nm, count rates of 1.6 MHz and positive key rates over 175 km of telecom fibre are achieved. The researchers use a tighter multiplicative Chernoff bound to constrain estimated finite key parameters, significantly reducing the required number of received signals.
NATURE COMMUNICATIONS
(2023)
Article
Physics, Multidisciplinary
S. M. Barnett, F. C. Speirits, J. B. Gotte
Summary: We demonstrate that skyrmion field lines, created using local Stokes parameters, follow lines of constant optical polarization.
Article
Optics
Amy McWilliam, Claire M. Cisowski, Zhujun Ye, Fiona C. Speirits, Jorg B. Gotte, Stephen M. Barnett, Sonja Franke-Arnold
Summary: The skyrmion number of paraxial optical skyrmions can be defined through their polarization singularities and associated winding numbers, using Stokes's theorem. This definition provides a robust method to extract the skyrmion number from experimental data, demonstrated for various optical skyrmions and bimerons and multi-skyrmions. This method not only increases accuracy but also offers an intuitive geometrical approach to understanding the topology of these light quasi-particles and their resistance to smooth transformations.
LASER & PHOTONICS REVIEWS
(2023)
Article
Optics
U. Zanforlin, G. Tatsi, J. Jeffers, G. S. Buller
Summary: Ghost imaging research has shown that it is possible to replicate an image of an object without interacting with the imaging light. In this paper, the authors theoretically describe and experimentally demonstrate a coherent displacement imposed on a two-mode state, replicating the ghost imaging effect in the coherent-state basis. They use this displacement operation to show the possibility of covert information sharing. This operation also has a secondary probabilistic amplification effect on the mean photon number, which could be utilized in covert quantum illumination experiments.
Proceedings Paper
Quantum Science & Technology
Gioan Tatsi, Ugo Zanforlin, Gerald S. Buller, John Jeffers
Summary: This study introduces a technique to imprint a nonlocal coherent amplitude onto a beam of light with thermal statistics, where the average phase information is unknown. The researchers have successfully conducted the first experimental realization of this technique, which may have applications in quantum information sharing and covert quantum imaging scenarios.
QUANTUM TECHNOLOGIES 2022
(2022)
Article
Optics
Hector Spencer-Wood, John Jeffers, Sarah Croke
Summary: The study explores measurement disturbance tradeoffs in quantum machine learning protocols, focusing on the simplest example of binary classification in the unsupervised regime. Surprisingly, different strategies for the first classification do not affect the success rate of the second classification, but there is a nontrivial measurement disturbance tradeoff between the success rates of the two classifications.
Article
Optics
G. Tatsi, D. W. Canning, U. Zanforlin, L. Mazzarella, J. Jeffers, G. S. Buller
Summary: Thermal radiation plays a crucial role in the development of quantum physics and has practical applications in quantum imaging and quantum illumination. This article introduces a method for manipulating thermal states of light using a generalized photon subtraction scheme, and experimental results demonstrate its feasibility.
Article
Optics
Niclas Westerberg, Anette Messinger, Stephen M. Barnett
Summary: This article discusses the form of magnetic interaction energy and its impact on atom-light properties. It proposes restoring the symmetry of Maxwell's equations through the inclusion of general local-field effects and emphasizes the necessity of correctly translating between the macroscopic and microscopic worlds, as well as its influence on the form of dipole forces in a medium.
Article
Optics
Craig S. Hamilton, Regina Christ, Sonja Barkhofen, Stephen M. Barnett, Igor Jex, Christine Silberhorn
Summary: Many photonic quantum information tasks use single photons and linear transformations for processing information. Integrated optical systems provide useful platforms for these tasks. Nonlinear-waveguide array systems are new technologies that enable multimode quantum operations and can generate highly nonclassical photon states.
