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Digital synthesis of programmable photonic integrated circuits

Chinese Physics B 2022年第2期31卷 355-365页

作者： Juan Zhang Zhengyong Ji Yipeng Ding Yang Wang Key Laboratory of Specialty Fiber Optics and Optical Access Networks School of Communication and Information EngineeringShanghai UniversityShanghai 200444China School of Physical Science and Electronics Central South UniversityChangsha 410012China Shanghai Institute of Optics and Fine Mechanics Chinese Academy of SciencesShanghai 201800China

Programmable photonic waveguide meshes can be programmed into many different circuit topologies and thereby provide a variety of *** to the complexity of the signal routing in a general mesh,a particular synthesis algorithm often only accounts for a specific function with a specific cell *** this paper,we try to synthesize the programmable waveguide mesh to support multiple configurations with a more general digital signal processing *** show the feasibility of this technique,photonic waveguide meshes in different configurations(square,triangular and hexagonal meshes)are designed to realize optical signal interleaving with arbitrary duty *** digital signal processing(DSP)approach offers an effective pathway for the establishment of a general design platform for the software-defined programmable photonic integrated *** use of well-developed DSP techniques and algorithms establishes a link between optical and electrical signals and makes it convenient to realize the computer-aided design of optics–electronics hybrid systems.

关键词： photonic integrated circuit digital signal processing Z-transform

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End-to-end aperture layout optimization and image restoration for optical sparse aperture systems

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OPTICS LETTERS 2023年第10期48卷 2504-2507页

作者： Zhao, Wenxiu Zhang, Xiaofang Beijing Inst Technol Sch Opt & Photon Beijing 100081 Peoples R China

The optical sparse aperture (OSA) imaging technique is capable of improving the spatial resolution of a telescope while maintaining lower size, weight, and cost. The major-ity of OSA system researches separately focus on the design optimization of aperture layout and the method for image restoration, which have great design redundancy. In this Letter, an end-to-end design framework that simultaneously optimizes the aperture layout parameters of the OSA sys-tem and neural network parameters of image restoration is proposed, which achieves excellent imaging quality. The results show that adequate image mid-frequency informa-tion captured by the OSA system benefits network processing more than incomplete high-frequency information in a few directions. Based on this framework, we design a simplified OSA system on geostationary orbit. The simulation results show that our simplified OSA system with six sub-apertures measuring 1.2m each has a comparable imaging perfor-mance to a single-aperture system measuring 12 m. (c) 2023 Optica Publishing Group

关键词： Fast Fourier transforms Image processing Image processing algorithms Image quality Image restoration Spatial resolution

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Methods and algorithms for computer synthesis of holographic elements to obtain a complex impulse response of optical information processing systems based on modern spatial light modulators

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QUANTUM ELECTRONICS 2020年第7期50卷 643-652页

作者： Zlokazov, E. Yu Natl Res Nucl Univ MEPhI Kashirskoe Sh 31 Moscow 115409 Russia

The possibilities of designing optical devices for data processing and imaging based on the manipulation of coherent light beams by means of spatial light modulators (SLMs) are investigated. A review of commercially available SLMs is presented and the limitations of their complex modulation characteristics are analysed. The main problem of using present-day SLMs is the lack of the ability to modulate directly all states within a unit circle in the complex plane. In this regard, the characteristics of current methods for the synthesis of holographic elements are described that implement a given complex impulse response of the optical system and are optimal for using SLMs with purely amplitude, purely phase, and hybrid amplitude - phase modulation.

关键词： computer holographic synthesis optical processing of information spatial light modulators

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Dual threshold demodulation algorithm for ultraviolet optical communication under turbulent channels

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OPTICS LETTERS 2025年第6期50卷 1819-1822页

作者： Cao, Fengyu Yang, Tao Ai, Yuxuan Zhang, Zhiguo Beijing Univ Posts & Telecommun State Key Lab Informat Photon & Opt Commun Beijing 100876 Peoples R China

In this paper, a novel, to the best of our knowledge, signal demodulation algorithm is proposed for the problem of severe scintillation of the received optical irradiance due to turbulence in ultraviolet (UV) communication scenarios. The algorithm innovatively proposes a signal probability model based on the UV turbulence characteristic and derives the optimal solution with dual judgment thresholds. The algorithm can provide a low bit error rate (BER) in scenarios with long distances and large elevation angles and solves the problem of severe degradation of demodulating performance of traditional algorithms, especially in a moderate and strong turbulence channel. A UV LED-based off-line experimental communication system capable of kilometer-scale transmission is established, and the system performance using the algorithm is validated in a 1000 m scenario for the first time to our knowledge and compared with typical traditional demodulation schemes. The results show that the algorithm proposed in this paper has a strong ability to resist the influence of atmospheric turbulence, as it reduces the BER by nearly four orders of magnitude relative to the traditional demodulation algorithm. It effectively improves the performance of UV communication in a strong turbulence scenario. (c) 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Atmospheric turbulence optical signals optical wireless communication Signal processing systems design Total internal reflection

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Fusion feature multi-objective classification algorithm based on adaptive scale feature residual network 16

Fusion feature multi-objective classification algorithm base...

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16th International Conference on Signal processing systems, ICSPS 2024

作者： Hua, Chenyang Xie, Renhong Li, Peng Fang, Gan Zhao, Xianya Zhou, Maoyuan School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China

ISBN: (纸本)9781510689251

With the development of science and technology, radar has been widely used in both civil and military fields, and radar target classification and recognition is an important research direction in radar signal processing field. The traditional classification and recognition technology does not utilize all the information of echo, and the recognition rate will decrease obviously when the environment is too complicated and the SNR is low. To solve the above problems, this paper proposes three recognition algorithms. It is a fusion feature multi-objective classification algorithm based on multi-scale feature residual network (MKRN), a fusion feature multi-objective classification algorithm based on adaptive scale feature residual network (AKRN) and a fusion feature multi-objective classification algorithm based on adaptive scale feature multi-level branch residual network (AKSRN). These three algorithms introduce residual structure to avoid network degradation caused by the deepening of network depth, and use convolution kernel of different sizes to enhance the ability of the network to extract multi-scale feature information, which improves the accuracy of network classification and recognition. © 2025 SPIE.

关键词： Radar signal processing

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Highly Dynamic visual SLAM Dense Map Construction Based on Indoor Environments

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IEEE ACCESS 2024年 12卷 38717-38731页

作者： Mei, Jianfeng Zuo, Tao Song, Dong Wuhan Univ Sci & Technol Coll Informat Sci & Engn Wuhan 430081 Hubei Peoples R China Wuhan Univ Sci & Technol Engn Res Ctr Met Automat & Detecting Technol Minist Educ Wuhan 430081 Peoples R China

In indoor highly dynamic scenes or scenes with missing a priori dynamic information, most current schemes cannot effectively avoid the impact of moving objects on the performance of SLAM (Simultaneous Localization and Mapping) systems. In order to solve the problem of accurate localization and map building for mobile robots in indoor highly dynamic environments, we propose a dynamic RGB-D visual SLAM dense map building method based on pyramidal L-K (Lucas-Kanade) optical flow with multi-view geometric constraints. Our proposed method consists of three stages: dynamic object culling, camera position estimation, and dense map construction based on the TSDF (truncated signed distance function) model. First, dynamic elements in the scene are detected and culled by combining pyramidal L-K optical flow with a multi-view geometric constraint method. Then, the estimation of the camera pose is achieved by minimizing the SDF error function. Finally, the estimated camera poses and static depth images are used to construct TSDF dense maps and indexed using dynamic voxel assignment and spatial hashing techniques. We evaluated our method on dynamic sequences of the Bonn dataset and the TUM dataset, and proved the effectiveness of the algorithm on a real scene dataset of our own making. The experimental results show that our method can effectively improve the camera position estimation accuracy and realize the construction of dense maps after processing dynamic objects, which improves the robustness of the system as well as the accuracy of environment reconstruction.

关键词： Indoor environment Cameras Simultaneous localization and mapping optical flow Heuristic algorithms Robot vision systems Mobile robots Pose estimation Image analysis Dense construction dynamic object culling SLAM system trajectory estimation

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Metasurface-empowered optical cryptography

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MATERIALS TODAY 2023年第1期67卷 424-445页

作者： Yang, Hui Ou, Kai Wan, Hengyi Hu, Yueqiang Wei, Zeyong Jia, Honghui Cheng, Xinbin Liu, Na Duan, Huigao Hunan Univ Coll Mech & Vehicle Engn Natl Res Ctr High Efficiency Grinding Changsha 410082 Peoples R China Tongji Univ Inst Precis Opt Engn Sch Phys Sci & Engn Shanghai 200092 Peoples R China Univ Stuttgart Phys Inst 2 Pfaffenwaldring 57 D-70569 Stuttgart Germany Hunan Univ Greater Bay Area Inst Innovat Guangzhou 511300 Guangdong Peoples R China

information security is of great importance in every aspect of life, spawning numerous modern cryptographic strategies to protect data from stealing and deciphering. Among them, optical encryption is an excellent candidate with regard to its unique features such as parallel processing, high speed, low-power consumption and the abundant degrees of freedom (DoFs) of the photon for information encoding and decoding. However, the optical cryptographic systems based on conventional optical components are commonly restricted to exploiting a limited number of photon dimensions. The advent of the metasurface, which is capable of manipulating photons with full DoFs at a subwavelength scale, provides a new generation of versatile platforms for optical encryption techniques. Having almost exhausted the existing DoFs for information multiplexing, considerable attention has been paid to exploring new encryption algorithms and encoding optical information with the time domain. Here, we review recent research efforts devoted to metasurface-empowered photon cryptography in the DoF space, the algorithm space, and the spatiotemporal domain. The design principles, typical encryption strategies and potential applications are introduced in detail. We also discuss the challenges and provide an outlook on this emerging field.

关键词： Metasurface Photon Encryption Light field modulation

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Structural-information-awareness-based regularization model for infrared image stripe noise removal

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JOURNAL OF THE optical SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND viSION 2024年第9期41卷 1723-1737页

作者： Zhang, He Qian, Weixian Xu, Yinghui Zhang, Kaimin Kong, Xiaofang Wan, Minjie Nanjing Univ Sci & Technol Sch Elect & Opt Engn Nanjing 210094 Peoples R China Nanjing Univ Sci & Technol Natl Key Lab Transient Phys Nanjing 210094 Peoples R China

Infrared images play a crucial role in military reconnaissance, security monitoring, fire detection, and other tasks. However, due to the physical limitations of detectors, an infrared image often suffers from significant stripe noise. The presence of stripe noise significantly degrades image quality and subsequent processing, making the removal of such noise indispensable. In this study, we propose, to our knowledge, a novel low-rank decomposition model to separate the stripe noise components in infrared images. In comparison with existing algorithms for removing infrared stripe noise, our method takes into account the distinctiveness between stripe noise and information components. For the stripe noise component, we describe a column gradient domain low-rank prior and standard deviation weighted group sparsity prior. For the image information component, we employ a structure-aware gradient sparsity prior to suppress stripes while preserving the structural features of images. During the iterative solution process, we utilize both an initial solution based on minimizing column differences and an iteration step- size strategy based on variable acceleration to accelerate convergence. To validate the effectiveness of our proposed method, we conduct experiments to compare it with other destriping algorithms, demonstrating the superiority of our method from the perspectives of both subjective evaluation and objective metrics. (c) 2024 Optica Publishing Group

关键词： Deep learning Imaging systems Imaging techniques Infrared detectors Infrared imaging Spatial filtering

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A Study on multi-scale landscape character extraction combining GIS and graphic processing algorithms 3

A Study on multi-scale landscape character extraction combin...

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3rd International Conference on Environmental Remote Sensing and Geographic information Technology, ERSGIT 2024

作者： Wang, Shuwei Liu, Yang Li, Guangqi Su, Xueying Wang, Sen Bai, Xuyong Center for Geophysical Survey China Geological Survey Langfang China Technology Innovation Center for Earth Near Surface Detection China Geological Survey China

ISBN: (纸本)9781510690219

This research presents an innovative approach to accurately extract multi-scale landscape characters by combining geographic information systems (GIS) and graphic processing algorithms. It is essential to recognize and analyze landscape characters at different scales. This study uses GIS advantages in spatial analysis and the K-Means clustering algorithm in image enhancement, feature extraction, image segmentation, and color quantification. Through image interpretation and deep learning, the distribution characteristics of buildings in Langfang City are obtained to provide guidance and suggestions for the future construction and development of the city. The proposed method covers data preparation, algorithm design, and system implementation. In addition, the future research direction of improving the method is also discussed, and the possibility of its application in other fields is explored. © 2025 SPIE.

关键词： Photointerpretation

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D²UF: Deep Coded Aperture Design and Unrolling Algorithm for Compressive Spectral Image Fusion

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL processing 2023年第2期17卷 502-512页

作者： Jacome, Roman Bacca, Jorge Arguello, Henry Univ Ind Santander Dept Phys Santander 680002 Spain Univ Ind Santander Dept Comp Sci Santander 680002 Spain

Compressive spectral imaging (CSI) has attracted significant attention since it employs synthetic apertures to codify spatial and spectral information, sensing only 2D projections of the 3D spectral image. However, these optical architectures suffer from a trade-off between the spatial and spectral resolution of the reconstructed image due to technology limitations. To overcome this issue, compressive spectral image fusion (CSIF) employs the projected measurements of two CSI architectures with different resolutions to estimate a high-spatial high-spectral resolution. This work presents the fusion of the compressive measurements of a low-spatial high-spectral resolution coded aperture snapshot spectral imager (CASSI) architecture and a high-spatial low-spectral resolution multispectral color filter array (MCFA) system. Unlike previous CSIF works, this paper proposes joint optimization of the sensing architectures and a reconstruction network in an end-to-end (E2E) manner. The trainable optical parameters are the coded aperture (CA) in the CASSI and the colored coded aperture in the MCFA system, employing a sigmoid activation function and regularization function to encourage binary values on the trainable variables for an implementation purpose. Additionally, an unrolling-based network inspired by the alternating direction method of multipliers (ADMM) optimization is formulated to address the reconstruction step and the acquisition systems design jointly. Finally, a spatial-spectral inspired loss function is employed at the end of each unrolling layer to increase the convergence of the unrolling network. The proposed method outperforms previous CSIF methods, and experimental results validate the method with real measurements.

关键词： Spatial resolution Image reconstruction Apertures Image coding Signal processing algorithms optical sensors optical imaging End-to-End Optimization Synthetic Aperture Design Compressive Spectral Image Fusion Unrolling algorithms

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