Article
Optics
Fang He, Rui Liu, Xin Tian
Summary: Imaging through scattering media has been a topic of interest, and existing studies are mostly focused on reconstructing objects from speckle patterns. This research proposes a robust scanning-based photon-limited imaging system, which eliminates aliasing effects and detects weak signals using a Geiger-mode avalanche photo diode. A blind deep-learning denoising framework is also introduced to handle the Poisson noise in the captured images. Real experiments demonstrate significant improvements in imaging quality.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Optics
Shanshan Zheng, Hao Wang, Shi Dong, Fei Wang, Guohai Situ
Summary: This study proposes a method for single-shot incoherent imaging through highly nonstatic and optically thick turbid media using a deep neural network, achieving high fidelity reconstruction of object images in severe environments with high turbidity.
PHOTONICS RESEARCH
(2021)
Article
Optics
Zhirun Wang, Wenjing Zhao, Aiping Zhai, Peng He, Dong Wang
Summary: An optimized sampling method using a Deep Q-learning Network (DQN) is proposed for single-pixel imaging, treating the sampling process as decision-making to obtain a relatively optimal sampling strategy for OT-SPI. The effectiveness of the method is verified through simulations and experiments, eliminating the influence of imperfect sampling path planning on imaging performance.
Article
Optics
Hang Liu, Yani Chen, Li Zhang, Da-Hai Li, Xiaowei Li
Summary: This research proposes a deep learning method for achieving color ghost imaging through scattering media. Experimental results demonstrate that the method can efficiently reconstruct color images with rich details, even at different scattering intensities.
Article
Engineering, Electrical & Electronic
Meiling Zhou, Chen Bai, Yang Zhang, Runze Li, Tong Peng, Jia Qian, Dan Dan, Junwei Min, Yuan Zhou, Baoli Yao
Summary: In this study, a deep-learning method based on the improved optical scheme is proposed to accelerate the data acquisition and image reconstruction speed of the shower-curtain effect and ptychography (PSE) for large field-of-view object reconstruction behind scattering media. By replacing the mechanical translation stage with a digital micromirror device (DMD), a large amount of training data can be collected, and single-shot pattern and sub-second reconstruction can be achieved. Qualitative and quantitative analysis on binary resolution target and 2D biological slide specimens demonstrate the effectiveness and feasibility of the proposed method, showing promising applications in tissue imaging.
IEEE PHOTONICS TECHNOLOGY LETTERS
(2022)
Article
Computer Science, Interdisciplinary Applications
Ya Gao, Wenyi Xu, Yiming Chen, Weiya Xie, Qian Cheng
Summary: In this study, a convolutional neural network based on U-Net was developed to extract effective photoacoustic information from speckle patterns obtained under porous media, enabling the reconstruction of high-quality vessel images. The proposed deep learning-based algorithm outperforms traditional reconstruction methods.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2022)
Article
Optics
Yiwei Sun, Xiaoyan Wu, Yuanyi Zheng, Jianping Fan, Guihua Zeng
Summary: This paper explores dynamic scattering imaging under photon-limited conditions, developing a scalable imaging method that successfully achieves real-time recovery of high-quality images using an average of only about 0.4 valid detected photons per pixel. The method demonstrates robust performance in dynamic media, with good effects on lighting intensities and perturbations, and is suitable for a wide range of statistical variations.
OPTICS AND LASERS IN ENGINEERING
(2021)
Article
Optics
Bapan Debnath, M. S. Meena, Jayashree A. Dharmadhikari, Saptarishi Chaudhuri, Reji Philip, Hema Ramachandran
Summary: In this paper, a novel technique for improving image visibility is proposed, which utilizes the quadrature lock-in discrimination algorithm with the demodulation performed using an acousto-optic modulator. Significant enhancement in image visibility is achieved by processing a series of frames. The effect of camera parameters on enhancing image visibility is investigated through systematic imaging.
Article
Optics
Alexander Groeger, Giancarlo Pedrini, Daniel Claus, Igor Alekseenko, Felix Gloeckler, Stephan Reichelt
Summary: In this paper, the authors demonstrate digital holographic imaging through a 27-m-long fog tube filled with ultrasonically generated fog, showing its potential for imaging through scattering media. The results indicate that holographic imaging requires significantly less illumination power compared to conventional imaging for the same imaging range. They also provide a simulation model and quantitative analysis on the influence of various physical parameters on the imaging range.
Article
Optics
Huichuan Lin, Cheng Huang, Zhimin He, Jun Zeng, Fuchang Chen, Chaoqun Yu, Yan Li, Yongtao Zhang, Huanting Chen, Jixiong Pu
Summary: This paper presents an approach for phase imaging through scattering media using an incoherent light source, by training a Convolutional Neural Network (CNN) to reconstruct target images from captured speckle images. Over 90% similarities between reconstructed and target images were achieved. It concludes that an incoherent light source can be used for scattering phase imaging with the assistance of deep learning technology.
Article
Multidisciplinary Sciences
Shuhui Li, Simon A. R. Horsley, Tomas Tyc, Tomas Cizmar, David B. Phillips
Summary: The article discusses the nature of optical memory effects in structures of arbitrary geometry and proposes a framework to estimate the transmission matrix of an optical fiber from just one end through feedback.
NATURE COMMUNICATIONS
(2021)
Article
Optics
Enlai Guo, Yi Wei, Shuo Zhu, Lianfa Bai, Jing Han
Summary: In this paper, a color imaging method for reconstructing objects hidden behind scattering media is proposed. The method is based on the irrelevance between speckles of different wavelengths and speckle correlation imaging. It separates the speckles of different wavelengths and reconstructs them using the phase retrieval algorithm, providing an effective approach for color imaging through scattering media.
OPTICS AND LASERS IN ENGINEERING
(2023)
Article
Optics
Yuanzhi Zhao, Wenjun He, Hang Ren, Yahong Li, Yuegang Fu
Summary: In this study, the traditional polarization imaging model's limitations are overcome by adding constraints, and a new method is proposed to simultaneously obtain the polarization information of the target and scattering medium. The method demonstrates high contrast and similarity to targets without scattering in underwater imaging.
OPTICS AND LASERS IN ENGINEERING
(2022)
Article
Optics
Jiahuan Li, Zijing Zhang, Mingwei Huang, Jiaheng Xie, Fan Jia, Liping Liu, Yuan Zhao
Summary: Benefiting from deep learning, we propose a non-invasive imaging method through scattering media using dual-cycle Generative Adversarial Networks (GANs). This method can perform image translation between speckle images and object images without the need for alignment, and reconstruct clear object images with the help of a pre-trained convolutional neural network.
OPTICS COMMUNICATIONS
(2022)
Article
Physics, Applied
Lina Zhou, Yin Xiao, Wen Chen
Summary: In this Letter, a setup design is presented for achieving high-visibility orthonormalized ghost imaging (GI) with self-correction through dynamic and complex scattering media at low sampling ratios. The design incorporates parallel detection to correct the mismatch between illumination patterns and intensity measurements. Moreover, Gram-Schmidt orthonormalization is applied to the corrected intensities and illumination patterns to enable high-visibility GI through dynamic and complex scattering media at low sampling ratios. Experimental results demonstrate that the proposed self-correction and orthonormalization methods enable high-visibility and high-efficiency GI through dynamic and complex scattering media at low sampling ratios. This method offers a promising alternative for achieving high-visibility object reconstruction through dynamic and complex scattering media at low sampling ratios, addressing a challenge faced by conventional GI techniques.
APPLIED PHYSICS LETTERS
(2023)
Article
Optics
Ryoichi Horisaki, Takuro Aoki, Yohei Nishizaki, Andre Rohm, Nicolas Chauvet, Jun Tanida, Makoto Naruse
Summary: In this paper, wave propagation models of spatially partially coherent light are presented to reduce the computational load of forward and back propagations in inverse problems. By approximating partially coherent light as random or plane wavefronts passing through spatial filters, the number of coherent propagations can be reduced, making it applicable in optical control and sensing.
Article
Optics
Ryoichi Horisaki, Kunihiko Ehira, Yohei Nishizaki, Makoto Naruse, Jun Tanida
Summary: This paper presents a technique for digital optical phase conjugation through scattering media using spatially and temporally incoherent light. The method eliminates the need for light coherence and interferometric measurement, and includes a method for suppressing background noise.
Article
Optics
Hideyuki Muneta, Ryoichi Horisaki, Yohei Nishizaki, Makoto Naruse, Jun Tanida
Summary: This paper presents a method for single-shot blind deconvolution incorporating a coded aperture. The method utilizes the coded aperture inserted on the pupil plane as support constraints, estimating both the object and the turbulence point spread function from a single captured image using a reconstruction algorithm with coded aperture support. The proposed method is demonstrated through simulation and an experiment, successfully recovering point sources under severe turbulence conditions.
Article
Optics
Ryutaro Suda, Makoto Naruse, Ryoichi Horisaki
Summary: This paper presents a method for computer-generated holography using spatially and temporally incoherent light. The proposed method synthesizes a hologram cascade by solving an inverse problem for the propagation of incoherent light, removing speckle noise in CGH and simplifying the optical setup.
Article
Optics
Ryoichi Horisaki, Kaoru Yamazaki, Yohei Nishizaki, Makoto Naruse, Jun Tanida
Summary: In this paper, a method for single-shot phase imaging with a wide field of view based on coherent diffraction imaging is proposed. By introducing a shift-invariant scattering process, the limited field of view is extended and imaging performance is improved. This method is implemented by inserting a scattering plate on the pupil plane in an imaging system.
Article
Physics, Multidisciplinary
Naoki Fujita, Andre Rohm, Takatomo Mihana, Ryoichi Horisaki, Aohan Li, Mikio Hasegawa, Makoto Naruse
Summary: In this study, we prove the existence of algebraic structures in the pairing problem and minimize the variance of individual compatibilities by transforming the initially estimated compatibility information. We demonstrate that the total compatibility obtained using the heuristic pairing algorithm on the transformed problem is significantly higher than the previous method. With this improved perspective, we can contribute to practical applications such as wireless communications.
Article
Mathematics, Applied
Kohei Tsuchiyama, Andre Rohm, Takatomo Mihana, Ryoichi Horisaki, Makoto Naruse
Summary: Reservoir computing is a machine learning paradigm that utilizes a reservoir structure with nonlinearities and short-term memory. It has expanded to various functions including autonomous generation of chaotic time series, time series prediction, and classification. Sampling plays a crucial role in physical reservoir computers, but finding the suitable sampling frequency is essential for effectively regenerating chaotic time series.
Article
Mathematics, Applied
Naoki Asuke, Tomoki Yamagami, Takatomo Mihana, Andre Rohm, Ryoichi Horisaki, Makoto Naruse
Summary: Multiscale entropy (MSE) and Allan variance are statistical measures used to study nonlinear systems at different time scales. Despite being developed independently for different purposes, they share foundations and exhibit similar tendencies from an information-theoretical perspective. Experimental results show that MSE and Allan variance demonstrate similar properties in chaotic lasers and physiological heartbeat data. The consistency between MSE and Allan variance is related to certain conditional probabilities. However, artificially constructed random sequences demonstrate different trends in MSE and Allan variance.
Article
Mathematics, Interdisciplinary Applications
Hiroaki Shinkawa, Nicolas Chauvet, Guillaume Bachelier, Andre Rohm, Ryoichi Horisaki, Makoto Naruse
Summary: When faced with multiple choices, personal preferences often lead to conflicts and losses when others make the same selections. Previous studies focused on fair joint decision-making with deterministic preferences, while our research proposes conflict-free joint decision-making that satisfies the probabilistic preferences of all players.
Article
Physics, Multidisciplinary
Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana, Andre Rohm, Ryoichi Horisaki, Makoto Naruse
Summary: Quantum walks have the unique ability to exhibit both linear spreading and localization, which is utilized in various applications. This paper proposes algorithms for multi-armed bandit problems using both classical random walks and quantum walks. By associating the difficult operations of exploration and exploitation with the behaviors of quantum walks, we show that the quantum walk model outperforms the corresponding random walk model under certain settings.
Article
Physics, Applied
Hirotsugu Suzui, Kazuharu Uchiyama, Kingo Uchida, Ryoichi Horisaki, Hirokazu Hori, Makoto Naruse
Summary: A mathematical model based on swallow-tail catastrophe is proposed to explain the diverse morphological changes observed in photochromic crystals. This model can classify and explain bending, cracking, and photosalient effects, and provides insight into unexplored operating conditions of the crystals.
JOURNAL OF APPLIED PHYSICS
(2023)
Article
Optics
Ryutaro Suda, Yohei Nishizaki, Makoto Naruse, Ryoichi Horisaki
Summary: We propose a method for computer-generated holography (CGH) that allows different images to be reproduced on both sides of a hologram using a single illumination source. This method utilizes a transmissive spatial light modulator (SLM) and a half mirror (HM) located downstream of the SLM. The light modulated by the SLM is partially reflected by the HM, and the reflected light is modulated again by the SLM for double-sided image reproduction. We derive an algorithm for double-sided CGH and demonstrate it experimentally.
Article
Optics
Takuto Igarashi, Makoto Naruse, Ryoichi Horisaki
Summary: We propose a diffractive optics design for incoherent imaging that allows for an extendable field-of-view. Our method uses multiple layers of DOEs to reproduce upright images from a spatially incoherent input plane onto an output plane, without the need for shift invariance approximation. The field-of-view can be extended by using an array of DOEs without further calculation.
Article
Optics
Tomoki Yamagami, Etsuo Segawa, Ken'ichiro Tanaka, Takatomo Mihana, Andre Rohm, Ryoichi Horisaki, Makoto Naruse
Summary: In this paper, we propose the existence of a common underlying structure, called a skeleton structure, in discrete-time quantum walks (QWs) on a one-dimensional lattice with a homogeneous coin matrix. This structure is independent of the initial state and partially independent of the coin matrix. It is best interpreted in the context of quantum-walk-replicating random walks (QWRWs), where it acts as a simplified formula for the transition probability. Additionally, we construct a random walk using the skeleton structure as transition probabilities and demonstrate its similarity to both the original QWs and QWRWs.
Article
Physics, Fluids & Plasmas
Naoki Asuke, Nicolas Chauvet, Andre Rohm, Kazutaka Kanno, Atsushi Uchida, Tomoaki Niiyama, Satoshi Sunada, Ryoichi Horisaki, Makoto Naruse
Summary: Allan variance is widely used to evaluate the stability of time series generated by atomic clocks and lasers, and it can also be beneficial in assessing chaotic oscillation dynamics of semiconductor lasers, especially in terms of low-frequency fluctuations. This study demonstrates the effectiveness of Allan variance in analyzing complex time series generated by semiconductor lasers with delayed feedback, particularly in capturing multiple time-scale dynamics, including low-frequency fluctuations. The findings suggest that Allan variance can provide insights into and characterize diverse laser dynamics spanning a wide range of timescales.
