最新刊期
卷 40 ， 期 12 ， 2025
- “液晶菲涅耳透镜技术在AR/VR、自适应光学等领域展现出重要应用价值，系统综述了其技术原理与发展现状。”摘要：Liquid crystal Fresnel lenses （LCFLs）， as electrically tunable optical elements， have demonstrated significant application potential in recent years in fields such as augmented reality （AR）/virtual reality （VR） and adaptive optics， owing to their compact structure， tunable focal length， and capacity for large apertures. This paper provides a systematic review of the technical principles and current development status of LCFLs， with a particular focus on their phase modulation mechanisms and methods for controlling optical properties. By comparing structural differences with conventional refractive lenses， the critical role of liquid crystal anisotropy and electric field response characteristics in achieving multi-level phase profile design is summarized. Furthermore， application cases of this technology in AR/VR near-eye displays， auto-stereoscopic display systems， and adaptive optics are discussed. Finally， prospects for the future development of LCFLs are presented.关键词：liquid crystal Fresnel lens;liquid crystal optical devices;electric control lens83|75|0更新时间：2025-12-24
- “最新研究揭示环境光对比度提升关键因素，专家建立量化模型，为高环境光下显示面板设计提供理论依据。”摘要：This article systematically analyzes the key factors affecting Ambient Contrast Ratio （ACR）， including external ambient illuminance and internal panel characteristics （such as display white-state luminance， black-state luminance， and reflectivity）， to clarify the contribution of each factor and propose targeted ACR improvement solutions. It provides a theoretical basis for the optimal design of display panels under high ambient light conditions. Using a controlled variable approach， simulation experiments were conducted by building an optical simulation model to examine the effects of ambient illuminance （100~1 000 lx）， panel luminance （200~900 cd/m2）， and the reflectivity of different materials （polarizer （POL）， black matrix （BM）， shielding layer ITO） on ACR. Experimental tests quantified the impact of each parameter and determined the weight relationships of the key factors. The research findings indicate： （1） Increased ambient light exponentially reduces ACR， but when panel luminance exceeds 500 cd/m2 and reflectivity is below 1.3%， ACR can still be maintained above 120∶1 under 1 000 lx； （2） ACR shows a significant linear positive correlation with panel luminance （R²>0.99）， a 50% increase in luminance results in an average 50% growth in ACR； （3） ACR is inversely proportional to panel reflectivity， lower reflectivity leads to higher ACR， with POL material having the dominant influence （contributing about 80%）， while BM and ITO together account for only 20%； （4） Black-state luminance has a negligible effect on ACR. Differentiated strategies for enhancing ACR include： （1） Prioritizing optimization of POL material （e.g.， using anti-reflection coatings） to reduce reflectivity by over 80%； （2） Setting a reasonable threshold for luminance increase （suggested 400~600 cd/m2） to balance power consumption； （3） Using BM/ITO optimization as a supplementary measure. The quantitative ACR model established in this study can provide direct guidance for the design of office display devices.关键词：ambient CR;environmental illumination;LCD white luminance;LCD black luminance;LCD reflectivity165|110|0更新时间：2025-12-24
- “液晶显示技术新突破，新型三栅极像素架构降低功耗26%，提升侧视角对比度55%，实现高画质显示。”摘要：The liquid crystal display （LCD） panel technology is increasingly growing with incompatible demands for image quality， power consumption and low cost. To meet the low-cost demand， increasing gate lines via Triple Gate pixel architecture， while it has drawbacks of high power consumption， low contrast ratio and poor image quality， is an effective way to reduce the number of integrated circuits （ICs）. Here， a generic new Triple Gate pixel architecture is verified with 26% power consumption reduction during solid-color display operation， 55% contrast ratio increase under 45o view angle and high image quality. It offers an innovative solution for improving the performance of low-cost LCD panels.关键词：new Triple Gate pixel architecture;display panel;array design82|72|0更新时间：2025-12-24
- “在柔性有机发光二极管领域，专家通过全因子实验设计，揭示了射频功率和电极间距对偏光片褪色行为的影响机制，为提升设备湿热环境下可靠性提供解决方案。”摘要：This study investigates the key factors in the plasma-enhanced chemical vapor deposition （PECVD） process for silicon nitride （SiNₓ） films to address the polarizer （POL） bleaching issue in flexible organic light-emitting diodes （OLEDs） under damp-heat conditions. A full factorial design of experiments was employed to systematically analyze the effects of radio frequency （RF） power and electrode spacing on film properties and polarizer bleaching behavior. The results demonstrate that both RF power （P=0.006） and electrode spacing （P=0.023） are significant factors affecting polarizer bleaching. The degree of bleaching exhibits a negative correlation with RF power and a positive correlation with electrode spacing， with the established linear model explaining 89.88% of the variation. No significant statistical association was found between film stress and polarizer bleaching （P=0.169）， indicating that both are parallel responses to process parameters. The total bonded hydrogen content （N—H and Si—H bonds） in SiNₓ films shows a strong positive correlation with polarizer bleaching （P=0.007， R2=79.1%）. As a key indicator of plasma dissociation capability， the voltage peak-to-peak （Vpp） value shows a significant negative correlation with bonded hydrogen content （P=0.015）. Increasing RF power and reducing electrode spacing significantly enhance Vpp， thereby effectively reducing the total bonded hydrogen content in SiNₓ films and promoting the formation of a denser， more stable film structure. This reduction in bonded hydrogen content decreases the amount of ammonia released through oxidative degradation of SiNₓ films under damp-heat conditions， consequently minimizing its reaction with iodine ions in the polarizer and ultimately inhibiting polarizer bleaching. These findings significantly enhance the reliability of flexible OLEDs in damp-heat environments.关键词：polarizer bleaching;plasma enhanced chemical vapor deposition;silicon nitride;RF power;electrode spacing;bonded hydrogen content;voltage peak-to-peak80|61|0更新时间：2025-12-24
Device Physics and Device Preparation
- “在元宇宙领域，专家构建了6种虚拟场景，验证了视听融合对沉浸感的影响，为提升虚拟场景沉浸感提供理论依据和实践参考。”摘要：As metaverse-related technologies continue to advance across domains， users are demanding ever-higher-quality virtual-reality experiences. How to enhance immersion in virtual scenes through audio-visual integration stimulation has therefore become a pivotal research direction for metaverse development. This study investigates the impact of audio-visual integration on VR immersion by constructing six virtual scenes that differ only in their type of audio-visual integration. A combined subjective-objective approach was adopted. Subjective immersion was obtained with the IPQ questionnaire completed immediately after each trial， whereas objective immersion was quantified from EEG signals recorded throughout the trial with a portable device. The experimental results demonstrate that different types of audio-visual integration exert a highly significant impact on the quantified subjective sense of immersion （p<0.001） and a significant impact on the quantified objective sense of immersion （p<0.01）. Moreover， there is an extremely strong positive correlation between subjective and objective data （r=0.990）. These findings provide both theoretical grounding and practical guidance for enhancing VR-scene immersion by improving audio-visual coherence.关键词：metaverse;virtual reality;audio-visual integration;immersion perception40|62|0更新时间：2025-12-24
- “科技媒体新闻记者报道：最新研究提出了一种结合角膜折射与下眼睑滑移补偿的凝视估计算法，有效提升头戴式眼动追踪系统的凝视估计精度和鲁棒性。”摘要：To improve the gaze estimation accuracy and slippage-robust in head-mounted eye tracking devices， a gaze estimation algorithm combining corneal refraction and lower eyelid slip compensation was proposed. First， an initial eye model was constructed based on the pupil back-projection method to obtain the virtual pupil position. The pupil positioning error caused by corneal refraction was corrected using the Snell refraction law to obtain the true pupil position. The optimized eye model was then iteratively obtained. Subsequently， vertical device slip was monitored in real time through lower eyelid region corner detection and density analysis to compensate for gaze estimation. Experimental results show that the proposed method can compensate for the slip effect when the device is worn， with an average gaze estimation error of 2.882°， which is superior to two-dimensional and three-dimensional methods. The proposed gaze estimation algorithm combining corneal refraction and lower eyelid slip compensation can effectively improve gaze estimation accuracy and significantly enhance the system’s robustness to device slip in real-world wearable scenarios， verifying the reliability and practicality of the proposed method.关键词：head-mounted display;gaze estimation;corneal refraction;slippage32|59|0更新时间：2025-12-24
Display Technology
- “在三维重建领域，研究者提出了一种FPGA硬件加速架构，实现了高效率、低功耗的三维测量系统。”摘要：To achieve a high-efficiency and low-power 3D reconstruction system， this paper proposes a hardware-accelerated architecture based on a field-programmable gate array（FPGA） that integrates the two-plus-one phase-shifting method with complementary Gray code. First， fringe patterns are captured through a camera control module， followed by caching and filtering processing. Subsequently， leveraging the parallel computing capability of FPGA， key algorithms including wrapped phase calculation， phase unwrapping， and 3D reconstruction are hardware-accelerated and optimized. Finally， the 3D point cloud data is transmitted to the host computer via a Gigabit Ethernet module for visualization， forming a complete 3D measurement system. Experimental results demonstrate that the proposed architecture processes a set of 11 fringe images with a resolution of 720
Circuit Design
- “在复杂场景图像融合领域，研究人员提出了一种基于自编码器结构的融合模型，有效提升了融合图像质量。”摘要：In complex scenarios， infrared and visible image fusion models often struggle to fully extract the characteristics of overall macro-structures （from infrared images） and local micro-details （from visible images）， as well as to achieve synergy between these elements， which degrades fusion quality. To address this problem， this paper proposes a collaborative fusion principle based on scale specialization and designs a new fusion model based on an autoencoder architecture. The encoder and decoder of the model adopt a convolutional neural network （CNN） architecture. The model utilizes the global dual-group attention mechanism： after grouping feature maps by length and width to extract information， the generated inter-group channel attention map can achieve weighting of the feature maps， thereby generating new feature maps containing more large-scale global structural information. The model utilises a convolution mechanism with multi-scale pooling and dilation， using receptive fields of different sizes and implementing global average and median pooling operations， to extract small-scale local features in the image. The model utilizes a decoder to integrate the large-scale structure and small-scale details of densely connected layers and skip connections， enabling them to synergistically fuse and reconstruct the fused image. The experimental results demonstrate that， on the MSRS and TNO datasets， compared to the best results of other methods， the information entropy， mean gradient， and edge intensity were improved by 0.95%， 6.28%， and 6.19%， and then by 1.75%， 13.51%， and 11.75% respectively. Spatial frequency increased by 4.61% on the MSRS dataset， second only to the MDLSR-RFM method on the TNO dataset. These results validate the improvement in the quality of merged images in complex scenarios， as well as the increased robustness and generalization of the model.关键词：infrared and visible image fusion;image enhancement;global dual-group attention;Dilated convolution62|70|0更新时间：2025-12-24
- “在柔性玻璃贴合封装工艺领域，研究者提出了FSL-YOLO11n算法，有效提升了导电粒子检测效率，为工业检测提供了高效方案。”摘要：To address challenges in detecting defects of conductive particles with varied shapes， uneven sizes， and blurred edges in Flex on Glass（FOG） packaging processes， as well as the inefficiency of manual visual inspection， this paper proposes FSL-YOLO11n， an improved lightweight object detection algorithm based on YOLO11n. The algorithm incorporates the following enhancements： a Feature Complementary Mapping（FCM） module is introduced into the backbone network to reduce parameter redundancy and enhance small object feature extraction through feature splitting， directional transformation， mapping complementarity， and fusion. By introduce medical image boundary processing strategies and dynamic mechanisms， a cross-scale feature dynamic aggregation network is constructed， leading to a new feature pyramid structure named STDA-FPN （Small Target Dynamic Aggregation FPN）. This structure incorporates a Selective Boundary Aggregation（SBA） module， DySample module， and DIGC （Dynamic Inception GLU ConvFormer） module to improve multi-scale feature aggregation. A Lightweight Shared Convolutional Quality Detection （LSCQD） head is designed to reduce computational resource consumption and further lightweight the model. Experimental results on a constructed conductive particle dataset show that FSL-YOLO11n reduces the number of parameters by 0.8M compared to YOLO11n， while improving precision， recall， mAP@0.5， and mAP@0.5：0.95 by 2.6%， 3%， 3.1%， and 2.7%， respectively. It also operates stably on edge devices. The algorithm achieves both lightweight performance and enhanced detection accuracy in experimental settings， providing an efficient and practical solution for industrial inspection applications.关键词：YOLO11;conductive particles;object detection;feature fusion;industrial inspection101|42|0更新时间：2025-12-24
- “在智能交通领域，研究者提出了改进的YOLOv8-NTS模型，有效提升了交通标志检测精度和泛化能力。”摘要：To address the low detection accuracy of current traffic sign detection methods for small， blurred targets and complex environments， this paper proposes an improved traffic sign detection model YOLOv8-NTS， to enhance recognition performance in complex traffic scenarios. The model incorporates three key enhancements over YOLOv8： First， it introduces the lightweight Hybrid Attention Transformer （SlimHAT） module within the backbone network to strengthen global pixel information modeling and improve feature representation accuracy. Second， it replaces the original C2f module with the WT-C2fBlock module based on WTConv， reducing model parameters by 12.2% while maintaining detection accuracy. Finally， a novel detection head RFAhead was designed by integrating spatial attention mechanisms with convolutional operations， optimizing feature extraction and fusion processes to further enhance the model’s object representation capability and robustness. Experiments on the TT100K traffic sign dataset demonstrate that compared to the baseline YOLOv8 model， the improved YOLOv8-NTS achieves significant performance gains： 6.5% increase in precision， 5.0% increase in recall， 7.3% improvement in mAP50， and 5.3% enhancement in mAP50~90. The proposed YOLOv8-NTS model substantially improves traffic sign detection accuracy and generalization capabilities while maintaining low computational cost， validating the method’s effectiveness and practical value. It provides reliable technical support for traffic sign recognition in intelligent transportation scenarios.关键词：traffic sign detection;SlimHAT;WT-C2fBlock;RFAhead;YOLOv8104|53|0更新时间：2025-12-24
- “在夜间低光照行人检测领域，研究者提出了基于改进RT-DETR的检测算法，有效提升了检测精度并降低了漏检率，具备良好的鲁棒性与实用性。”摘要：Pedestrian detection in low-light night-time environments faces challenges including high false positive rates， significant false negatives， and insufficient recognition accuracy. To address this， this paper proposes a detection algorithm based on an improved RT-DETR， achieving precise detection under low illumination through multi-module collaborative design. The algorithm embeds an FDT module at the top layer of the feature pyramid， employing a two-stage attention mechanism to enhance weak feature extraction and global context modelling capabilities. A DySample module is deployed in the neck network， employing a dynamically learnable spatial resampling mechanism to achieve multi-scale feature alignment and small object detection enhancement. Furthermore， the DRBC3 module serves as the feature extraction core， integrating multi-expansion-rate convolutions and re-parameterisation techniques to construct multi-scale receptive fields， thereby enhancing the capture of details in blurred and occluded objects. Experiments on the LLVIP dataset demonstrate that this algorithm achieves a 1.39% increase in mAP0.5， a 2.21% rise in Precision， and a 3% improvement in Recall， while simultaneously reducing the number of parameters. Inference speed is also significantly enhanced. Generalisation experiments on the NightSurveillance and Nightowls datasets further validate its superior performance. The algorithm effectively improves detection accuracy and reduces false negatives while maintaining real-time capability， exhibiting robust and practical performance.关键词：pedestrian detection;RT-DETR;low light;attentional mechanism;multi-scale57|32|0更新时间：2025-12-24
- “在室内大规模稀疏点云语义分割领域，研究人员提出了一种新型网络结构，有效提升了全局结构建模能力与几何细节保持，为大规模点云的高效高精度语义分割提供了可扩展的解决方案。”摘要：In order to address the insufficient global structure modeling and poor geometric detail preservation in large sparse point clouds indoors， which cannot be applied to various scene issues directly， this paper proposes a novel network architecture that integrates Spatial Point Filling Serialization（SPFS） with Geometry-aware Channel Propagation（GCP）. The SPFS module employs an adaptive space-filling curve to order neighborhood points， explicitly preserving directional and spatial proximity information while reducing reliance on explicit coordinate encoding. The GCP module leverages geometric relationships between points to guide weighted channel interactions and residual fusion， thereby enhancing discrimination of complex structures and boundary regions. Experimental results show that the proposed method achieves superior performance across mainstream evaluation metrics，with particularly effective on challenging categories and small-scale targets. On the Stanford Large-Scale 3D Indoor Spaces（S3DIS） dataset， compared with RandLA-Net， our method improves
- “在手术导航领域，专家提出了光学-惯性混合位姿跟踪算法，有效解决了光路遮挡问题，提高了系统鲁棒性，对临床应用具有重要意义。”摘要：In the clinical application of surgical navigation systems， navigation pose information loss due to obstruction of the optical path is prone to occur because of the limited operating space in minimally invasive surgery. This limitation hinders the clinical application of surgical navigation systems. To address this issue， a hybrid optical-inertial pose tracking algorithm based on indirect Extended Kalman Filter is proposed. The algorithm uses an established error model as the state equation and constructs the measurement equation based on the pose obtained from the optical system， which is then applied to the extended Kalman filter for state prediction and measurement updates. When the optical path is not occluded， the optical system corrects and compensates for the error of the inertial system. When the optical path is occluded for a short period， the inertial system independently performs pose tracking to avoid the loss of surgical tool posture information. Experimental results show that under occlusion conditions， the hybrid tracking system maintains low levels of attitude angle errors （RMSE ≤ 0.322°， maximum error ≤ 0.877°） and positional errors （RMSE ≤ 0.525 mm， maximum error ≤ 1.385 mm） along all three axes. The designed system addresses the issue of navigation information loss caused by optical occlusion in surgical navigation systems， thereby enhancing their robustness. This advancement holds significant importance for promoting the clinical application of surgical navigation systems and improving the treatment standards of hospitals.关键词：surgical navigation;optical tracking system;inertial measurement unit;extended kalman filter45|20|0更新时间：2025-12-24
Image Processing
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