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Intelligent tailoring of a broadband orbital angular momentum comb towards efficient optical convolution

Photonics Research 2025年第5期13卷 1148-1157页

作者： Zhou, Shiyun Li, Lang Wang, Yishu Gao, Liliang Zhang, Zhichao Gao, Chunqing Fu, Shiyao School of Optics and Photonics Beijing Institute of Technology Beijing100081 China Key Laboratory of Photoelectronic Imaging Technology and System Ministry of Education Beijing100081 China Key Laboratory of Information Photonics Technology Ministry of Industry and Information Technology Beijing100081 China National Key Laboratory on Near-surface Detection Beijing100072 China

Due to the high-dimensional characteristics of photon orbital angular momentum (OAM), a beam can carry multiple OAMs simultaneously thus forming an OAM comb, which has been proved to show significant potential in both classical and quantum photonics. Tailoring broadband OAM combs on demand in a fast and accurate manner is a crucial basis for their application in advanced scenarios. However, obtaining phase-only gratings for the generation of arbitrary desired OAM combs still poses challenges. In this paper, we propose a multi-scale fusion learning U-shaped neural network that encodes a phase-only hologram for tailoring broadband OAM combs on-demand. Proof-of-principle experiments demonstrate that our scheme achieves fast computational speed, high modulation precision, and high manipulation dimensionality, with a mode range of −75 to +75, an average root mean square error of 0.0037, and a fidelity of 85.01%, all achieved in about 30 ms. Furthermore, we utilize the tailored broadband OAM combs in conducting optical convolution calculation, enabling vector convolution for arbitrary discrete functions, showcasing the extended capability of our proposal. This work opens, to our knowledge, new insight for on-demand tailoring of broadband OAM combs, paving the way for further advancements in high-dimensional OAM-based applications. © 2025 Chinese Laser Press.

关键词： Angular momentum

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Research on multi-layer lobster eye detection technology 10

Research on multi-layer lobster eye detection technology

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10th Symposium on Novel Optoelectronic Detection technology and Applications

作者： Ji, Fan Wang, JunYa Chang, Jun Zhang, YunQiang Key Laboratory of Photoelectronic Lmaging Technology and System of Ministry of Education of China School of Optics and Photonics Beijng Institute of Technology Beijng100081 China National Key Laboratory on Near-surface Detection Beijing100072 China National Key Laboratory of Air-based Information Perception and Fusion Luoyang471009 China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

This paper focuses on the imaging technology of multi-layer lobster vision system based on infrared band, aiming to develop a multi-layer lobster eye coordination optical system that can improve the energy concentration. By designing the structure of the lobster eye lens and using the ray tracing software for simulation analysis, the energy concentration of the center of the cross focal spot generated by the lens is analyzed in detail. The optical system of multi-layer lobster eye lens is also designed to achieve the goal of increasing the energy concentration of the system. The whole study not only optimizes the performance of the optical system, but also provides an important theoretical and practical basis for the future application of bionic optical systems. © 2025 SPIE.

关键词： Ray tracing

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Temporal multiplexing coding strategy for spatiotemporal compressed imaging 4

Temporal multiplexing coding strategy for spatiotemporal com...

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4th International Computational imaging Conference, CITA 2024

作者： Hao, Xiaowen Ke, Jun School of Optics and Photonics Beijing Institute of Technology Beijing100081 China Key Laboratory of Photo-electronic Imaging Technology and System Ministry of Education of China Beijing100081 China National Key Laboratory on Near-surface Detection Beijing100072 China

ISBN: (纸本)9781510688834

Spatiotemporal compressed imaging(STCI) aims to improve the spatial and temporal resolution of an imaging system simultaneously, which can effectively alleviate the mutual constraints between the two imaging resolutions. However, the development of STCI is limited by the effectively modulate target scenes in dual-domain, and by the back-end reconstruction process which doesn't work well for high compression ratio(CR). In this paper, we propose a temporal multiplexing coding strategy for STCI, which can effectively help the reconstruction algorithm for a large CR. Simulated experiments are implemented to demonstrate our idea. The proposed method can achieve nice spatiotemporal reconstructions with CR equal to 128:1, in which the spatial CR is 16:1 and the temporal CR is 8:1. © 2025 SPIE.

关键词： Image coding

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Optimizing object classification with single-pixel imaging and transformer networks 4

Optimizing object classification with single-pixel imaging a...

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4th International Computational imaging Conference, CITA 2024

作者： Cheng, Yin Liao, Yusen Sun, Xin Ke, Jun School of Optics and Photonics Beijing Institute of Technology Beijing100081 China Key Laboratory of Photo-electronic Imaging Technology and System Ministry of Education of China Beijing100081 China National Key Laboratory on Near-surface Detection Beijing100072 China

ISBN: (纸本)9781510688834

Traditional computer vision tasks rely on high-quality images for classification, but single-pixel imaging (SPI) uses compressive sensing with a bucket detector to simplify hardware and reduce costs. However, factors like atmospheric turbulence can degrade SPI image quality, lowering classification accuracy. To address this, a block-based single-pixel image-free transformer classification framework is proposed. It uses a learnable binary sampling matrix for flexible sampling during SPI and divides the measurements into blocks, which are processed by a transformer network. Each block is treated as a sequence element, allowing the transformer to capture spatial and contextual relationships. Experiments show strong robustness to atmospheric turbulence, achieving 87% classification accuracy even at a 1% sampling rate, making this method suitable for challenging environments. © 2025 SPIE.

关键词： Pixels

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FocusTrack: A Self-Adaptive Local Sampling Algorithm for Efficient Anti-UAV Tracking

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Wang, Ying Xu, Tingfa Li, Jianan Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Key Laboratory of Photoelectronic Imaging Technology and System Ministry of Education of China Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401135 China

Anti-unmanned aerial vehicle (UAV) tracking poses significant challenges, including small target sizes, abrupt camera motion, and cluttered infrared backgrounds. Existing tracking paradigms can be broadly categorized into global-based and local-based methods. Global-based trackers, such as SiamDT and SiamSTA, achieve high accuracy by scanning the entire field of view but suffer from excessive computational overhead, limiting real-world deployment. In contrast, local-based methods, including OSTrack and ROMTrack, efficiently restrict the search region but struggle when targets undergo significant displacements due to the abrupt camera motion. Through preliminary experiments, it is evident that a local tracker, when paired with adaptive search region adjustment (SRA), can significantly enhance the tracking accuracy, narrowing the gap between local and global trackers. To address this challenge, we propose FocusTrack, a novel framework that dynamically refines the search region and strengthens feature representations, achieving an optimal balance between computational efficiency and tracking accuracy. Specifically, our SRA strategy estimates the target presence probability and adaptively adjusts the field of view, ensuring the target remains within focus. Furthermore, to counteract feature degradation caused by varying search regions, the attention-to-mask (ATM) module is proposed. This module integrates the hierarchical information, enriching the target representations with fine-grained details. Experimental results demonstrate that FocusTrack achieves state-of-the-art performance, obtaining 67.7% area under curve (AUC) on AntiUAV and 62.8% AUC on AntiUAV410, outperforming the baseline tracker by 8.5% and 9.1% AUC, respectively. In terms of efficiency, FocusTrack surpasses global-based trackers, requiring only 30G MACs and achieving 143 frames/s with FocusTrack (SRA) and 44 frames/s with the full version, both enabling real-time tracking. © 1980-2012 IEEE.

关键词： Object tracking

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Evetac Meets Sparse Probabilistic Spiking Neural Network: Enhancing Snap-Fit Recognition Efficiency and Performance

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IEEE Robotics and Automation Letters 2025年第6期10卷 5353-5360页

作者： Fang, Senlin Ding, Haoran Liu, Yangjun Liu, Jiashu Zhang, Yupo Li, Yilin Kong, Hoiio Yi, Zhengkun Faculty of Data Science City University of Macau 999078 China Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Shenzhen518055 China City University of Hong Kong Hong Kong University of Macau 999078 China Shenzhen Institute of Advanced Technology Shenzhen518055 China City University of Macau 999078 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China City University of Macau Faculty of Data Science 999078 China Chinese Academy of Sciences Key Laboratory of Biomedical Imaging Science and System Shenzhen518055 China

Snap-fit peg-in-hole assembly is common in industrial robotics, particularly for 3 C electronics, where fast and accurate tactile recognition is crucial for protecting fragile components. Event-based optical sensors, such as Evetac, are well-suited for this task due to their high sparsity and sensitivity in detecting small, rapid force changes. However, existing research often converts event data into dense images and processing them with dense methods, leading to higher computational complexity. In this letter, we propose a Sparse Probabilistic Spiking Neural Network (SPSNN) that utilizes sparse convolutions to extract features from the event data, avoiding computations on non-zero cells. We introduce the Forward and Backward Propagation Through Probability (FBPTP) method, which enables simultaneous gradient computation across all time steps, eliminating the need for the step-by-step traversal required by traditional Forward and Backward Propagation Through Time (FBPTT). Additionally, the Temporal Weight Prediction (TWP) method dynamically allocates weights for different time outputs, enhancing recognition performance with minimal impact on model efficiency. We integrate the Evetac sensor compactly into our robotic system and collected two datasets, named Tactile Event Ethernet (TacEve-Eth) and Tactile Event Type-C (TacEve-TC), corresponding to cantilever and annular snap-fit structures. Experiments show that the SPSNN achieves the superior trade-off between recognition performance and efficiency compared to other widely used methods, achieving the highest average recognition performance while reducing inference time by over 90% compared to FBPTT-based dense SNN baselines. © 2016 IEEE.

关键词： Robotic assembly

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Hyperspectral Remote Sensing Images Salient Object Detection: The First Benchmark Dataset and Baseline

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Liu, Peifu Bai, Huiyan Xu, Tingfa Wang, Jihui Chen, Huan Li, Jianan Beijing Institute of Technology Beijing100081 China Ministry of Education of China Key Laboratory of Photoelectronic Imaging Technology and System Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Big Data and Artificial Intelligence Laboratory Chongqing401151 China

The objective of hyperspectral remote sensing image salient object detection (HRSI-SOD) is to identify objects or regions that exhibit distinct spectrum contrasts with the background. This area holds significant promise for practical applications;however, progress has been limited by a notable scarcity of dedicated datasets and methodologies. To bridge this gap and stimulate further research, we introduce the first HRSI-SOD dataset, termed hyperspectral remote sensing saliency dataset (HRSSD), which includes 704 hyperspectral images (HSIs) and 5327 pixel-level annotated salient objects. The HRSSD dataset poses substantial challenges for SOD algorithms due to large-scale variation, diverse foreground-background relations, and multisalient objects. Additionally, we propose an innovative and efficient baseline model for HRSI-SOD, termed the deep spectral saliency network (DSSN). The core of DSSN is the cross-level saliency assessment block (CSAB), which performs pixel-wise attention and evaluates the contributions of multiscale similarity maps at each spatial location, effectively reducing erroneous responses in cluttered regions and emphasizes salient regions across scales. Additionally, the high-resolution fusion module (HRFM) combines bottom-up fusion strategy and learned spatial upsampling to leverage the strengths of multiscale saliency maps, ensuring accurate localization of small objects. Experiments on the HRSSD dataset robustly validate the superiority of DSSN, underscoring the critical need for specialized datasets and methodologies in this domain. Further evaluations on the HSOD-BIT and HS-SOD datasets demonstrate the generalizability of the proposed method. © 1980-2012 IEEE.

关键词： Optical remote sensing

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Design of off-axis reflective holographic optical elements in a holographic near-eye display system

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Optics letters 2025年第9期50卷 3022-3025页

作者： Zhang, Shijie Tian, Yifan Liu, Juan Beijing Engineering Research Center for Mixed Reality and Advanced Display MoE Key Lab of Photoelectronic Imaging Technology and System School of Optics and Photonics Beijing Institute of Technology Beijing 100081 China

Holographic optical elements (HOEs) span a wide application, such as virtual reality and augmented reality displays. However, due to the complex aperiodic structures in lens-type HOEs, the phase design faces difficulties in aberration optimization. Here, we present a method for the design of the off-axis reflective lens-type HOE. Considering the varying degrees of aberrations introduced by the varying object distances across different regions of the object plane, a straightforward yet effective local aberration compensation method is carried out through superimposing different mutually perpendicular cylindrical lens phases at different positions of the HOE. The optimized phase distribution of the HOE can be directly obtained for fabrication like holographic printing. The numerical results show that the field curvature (FC) and the interval of the imaging distance between the meridional plane and the sagittal plane are significantly reduced to 1% of their initial values, and the astigmatism is alleviated. The optical experiments are conducted using two spatial light modulators (SLMs), and the experimental results are in good agreement with the optimized ones. It is expected that the proposed method could be further applied for the development of holographic near-eye display (NED) devices.

关键词： Augmented reality Cylindrical lenses Display technology Holographic displays Near eye displays Spatial light modulators

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Infrared small target detection based on spatial attention density peaks searching

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Optoelectronics Letters 2025年第2期21卷 90-96页

作者： RAO Junmin LU Siyu LIU Shijian LI Fanming CAS Key Laboratory of Infrared System Detection and Imaging Technology Shanghai Institute of Technical PhysicsShanghai 200083China University of Chinese Academy of Sciences Beijing 100049China Shanghai Institute of Technical Physics Chinese Academy of SciencesShanghai 200083China School of Information Science and Technology ShanghaiTech UniversityShanghai 201210China

The detection of small targets poses a significant challenge for infrared search and tracking (IRST) systems,as they must strike a delicate balance between accuracy and *** this paper,we propose a detection algorithm based on spatial attention density peaks searching (SADPS) and an adaptive window selection ***,the difference-of-Gaussians (DoG) filter is introduced for preprocessing raw infrared ***,the image is processed by ***,an adaptive window selection scheme is applied to obtain window templates for the target scale ***,the small target feature is used to enhance the target and suppress the ***,the true targets are segmented through a *** experimental results show that compared with the seven state-of-the-art small targets detection baseline algorithms,the proposed method not only has better detection accuracy,but also has reasonable time consumption.

关键词： template searching Infrared

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In situ holistic optimization method for a collinear reflection Mueller matrix imaging polarimeter

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Applied Optics 2025年第13期64卷 3438-3446页

作者： Ma, Xiang Wu, Jinxian Zhao, Zhe Wei, Xiaolin Li, Yanqiu Key Laboratory of Photoelectronic Imaging Technology System of Ministry of Education of China School of Optics and Photonics Beijing Institute of Technology 5 South Zhongguancun Street Beijing100081 China Institute of Engineering Medicine Beijing Institute of Technology 5 South Zhongguancun Street Beijing100081 China

In this paper, we propose an in situ holistic optimization method for a collinear reflection Mueller matrix imaging polarimeter (CRMMIP). Traditional instrument matrix optimization approaches for CRMMIP have often neglected the polarization characteristics of non-polarization modulation elements, such as objectives, tube lenses, and beam splitters, leading to reduced instrument stability. To address this limitation, our method allows in situ determination of the Mueller matrices of non-polarization modulation elements, which are then combined with the instrument matrices model of the polarization state generator and analyzer to construct a holistic instrument matrix model. The improved model is used to optimize a more stable instrument matrix. The effectiveness of the proposed method is demonstrated through simulations and experimental verification. Additionally, we discuss the effects of dichroism and retardance in non-polarization modulation elements on instrument stability. © 2025 Optica Publishing Group.

关键词： Polarimeters

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