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A method of embedding a high-resolution image into a large field-of-view image

Multimedia Tools and Applications 2025年第14期84卷 13037-13056页

作者： Dong, Yanmei Pei, Mingtao Jia, Yunde Key Laboratory of Intelligent Information Processing and Graph Processing Tus College of Digit Guangxi University of Science and Technology Liuzhou545006 China Beijing Laboratory of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing100081 China

Images captured by wide-angle cameras or fisheye cameras are with large Field-of-View (FOV) but low resolution, while images captured by conventional cameras are with high-resolution but limited FOV. To handle this contradiction, in this paper, we propose to improve the resolution of a large FOV image by embedding a high-resolution image into it. We present an image embedding method based on non-rigid transformations and mesh optimization. Without any radial distortion correction on large FOV images, we utilize non-rigid transformations to model the mathematical transformation relationship between the high-resolution image and the large FOV image. Meanwhile, we exploit mesh optimization to generate evenly distributed control points for maintaining the shape and content of the large FOV image. To verify the effectiveness of the proposed method, we capture some image pairs from a conventional camera and a large FOV camera, and exploit several classic image alignment methods to implement four baseline methods. The experimental results show that our method preserves the shape and content of the original FOV image from 58% to 82%, which significantly outperforms all baseline methods. The results indicate that the proposed method can effectively embed a high-resolution image into a large FOV image as well as preserve the shape and content of the large FOV image. In other words, the resolution of a large FOV image can be improved via high-resolution image embedding. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Embeddings

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Surface-PMSM Sensorless Control Strategy Based on Reduced-Order Linear Kalman Filter Cooperating with Prediction Error Rolling Compensation

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IEEE Transactions on Power Electronics 2025年第8期40卷 10804-10815页

作者： Xu, Sang Shen, Anwen Tang, Qipeng Wang, Miaomiao Luo, Pan Luo, Xin Xu, Jinbang National Key Laboratory of Science and Technology on Multispectral Information Processing Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Wuhan430074 China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

Kalman filter (KF) is increasingly attracted for sensorless control of surface permanent magnet synchronous motors (SPMSMs) due to its strong robustness against measurement and system noise. However, conventional method suffers from poor position and speed estimation accuracy under dynamic conditions, and high computational cost. In order to solve these problems, an enhanced sensorless control strategy based on reduced-order linear Kalman filter (RLKF) cooperating with prediction error rolling compensation is introduced in this paper. Differing from conventional method, a reduced-order linear state equation encompassing rotor position, speed and torque disturbance is constructed. Then, by obtaining the prediction error of system output using the motor current equation in the predictive reference frame, the optimal estimation of rotor position and speed in KF algorithm is achieved based on the reduced-order model. This not only simplifies the calculation process, but also enhances the position and speed estimation accuracy under dynamic conditions. Meanwhile, a prediction error rolling compensation algorithm is developed to minimize the estimation deviations caused by motor parameters variations. Additionally, the system's dynamic performance is further improved with an adopted speed controller based on torque disturbance feedforward and acceleration feedback. Finally, experimental results verify the effectiveness and feasibility of the proposed strategy.1 © 1986-2012 IEEE.

关键词： Permanent magnets

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Metalens-based hybrid probe near-infrared endoscope objective

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Optics Express 2025年第3期33卷 5757-5768页

作者： Song, Yichen Mao, Shan Tang, Yufeng Zhao, Jianlin Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technology Shaanxi Key Laboratory of Optical Information Technology School of Physical Science and Technology Northwestern Polytechnical University Xi’an710129 China Shaanxi Key Laboratory of Optical Remote Sensing and Intelligent Information Processing Xi’an710119 China

Rapid large-area deep tissue imaging at long working distances is important for clinical diagnosis. A near-infrared metalens-based hybrid probe con-focal micro-endoscope (pCM) objective with a large field of view of 500 µm, a long working distance of 300 µm, and a small caliber of 2.2 mm was designed, which is compatible with conventional endoscopes to produce cell-resolution images of deep tissues. The performance of the metalens-based hybrid objective optical system was analyzed. Results show that the metalens-based hybrid pCM significantly improves the imaging quality of such optical systems under the premise of meeting the design accuracy requirements, which provides a new solution and an effective realization for the design of such optical systems. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Infrared devices

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Hybrid meta-optics facilitate an athermal continuous zoom optical system

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Optics Express 2025年第8期33卷 17121-17135页

作者： Tang, Yufeng Mao, Shan Song, Yichen Zhao, Jianlin Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technology Shaanxi Key Laboratory of Optical Information Technology School of Physical Science and Technology Northwestern Polytechnical University Xi’an710129 China Shaanxi Key Laboratory of Optical Remote Sensing and Intelligent Information Processing Xi’an710119 China

To meet the demand for continuous zoom capabilities in compact lenses over a wide temperature range, we designed a compact continuous zoom optical system based on hybrid meta-optics. This system can achieve thermal stability without additional heating or cooling across a broad temperature range, utilizing commonly available optical glass. It features a total length of just 9∼12 mm and comprises only 4 lenses. By incorporating metalens, the system effectively corrects chromatic aberration and off-axis distortion, while leveraging the thermal stability of these lenses to achieve passive thermal management. Analytical results demonstrate that the system is structurally compact, capable of smooth continuous zooming from -20∼+60 ℃ with a focal length range of 4.9∼9.8 mm, and maintains excellent imaging quality throughout (with a modulation transfer function greater than 0.5 at 100 lp/mm). Additionally, the zoom and tolerances are highly feasible. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Aberrations

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Positioning Error Compensation via Channel Knowledge Map for UAV Communication

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IEEE Internet of Things Journal 2025年第11期12卷 16977-16989页

作者： Zhang, Chiya Wang, Ting He, Chunlong Harbin Institute of Technology School of Electronic and Information Engineering Shenzhen518055 China Shenzhen University Guangdong Key Laboratory of Intelligent Information Processing Shenzhen518060 China

When Unmanned Aerial Vehicles (UAVs) perform high-precision communication tasks, such as searching for users and providing emergency coverage, positioning errors between base stations and users make it challenging to deploy trajectory planning algorithms. To address these challenges caused by position errors, a framework was proposed to compensate it by Channel Knowledge Map (CKM), which stores channel state information (CSI). By taking the positions with errors as input, the generated CKM could give a prediction of signal attenuation which is close to true positions. Based on that, the predictions are utilized to calculate the received power and a PPO-based algorithm is applied to optimize the compensation. After training, the framework is able to find a strategy that minimize the flight time under communication constraints and positioning error. Besides, the confidence interval is calculated to assist the allocation of power and the update of CKM is studied to adapt to the dynamic environment. Simulation results show the robustness of CKM to positioning error and environmental changes, and the superiority of CKM-assisted UAV communication design. © 2025 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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HRAM-VITON: High-Resolution Virtual Try-On with Attention Mechanism

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Computers, Materials & Continua 2025年第2期82卷 2753-2768页

作者： Yue Chen Xiaoman Liang Mugang Lin Fachao Zhang Huihuang Zhao College of Computer Science and Technology Hengyang Normal UniversityHengyang421002China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang421002China

The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on methods frequently encounter challenges, including misalignment between the body and clothing, noticeable artifacts, and the loss of intricate garment details. To overcome these challenges, we introduce a two-stage high-resolution virtual try-on framework that integrates an attention mechanism, comprising a garment warping stage and an image generation stage. During the garment warping stage, we incorporate a channel attention mechanism to effectively retain the critical features of the garment, addressing challenges such as the loss of patterns, colors, and other essential details commonly observed in virtual try-on images produced by existing methods. During the image generation stage, with the aim of maximizing the utilization of the information proffered by the input image, the input features undergo double sampling within the normalization procedure, thereby enhancing the detail fidelity and clothing alignment efficacy of the output image. Experimental evaluations conducted on high-resolution datasets validate the effectiveness of the proposed method. Results demonstrate significant improvements in preserving garment details, reducing artifacts, and achieving superior alignment between the clothing and body compared to baseline methods, establishing its advantage in generating realistic and high-quality virtual try-on images.

关键词： Virtual try-on attention mechanism high-resolution image generation

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Deep semantic network for hyperspectral image classification using enhanced bifurcation and light self-Gaussian attention mechanism

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Journal of Applied Remote Sensing 2025年第1期19卷

作者： Wan, Xiaoqing Chen, Feng He, Yupeng Hengyang Normal University College of Computer Science and Technology Hengyang China Hunan Provincial Key Laboratory of Intelligent Information Processing and Application Hengyang China

Convolutional neural networks (CNNs) are widely used in hyperspectral image (HSI) classification due to their strong feature extraction capabilities. Nevertheless, CNN-based classification methods face challenges in capturing deep semantic features effectively, and as the number of layers increases, computational expenses escalate significantly. In addition, spatial locations and spectral bands in HSI data have varying discriminative power. To address these challenges, we propose a novel approach, DSNet, which integrates a multiway attention mechanism with a CNN-based deep semantic network to improve HSI classification. First, we extract shallow abstract features using a module that combines 3D and 2D convolution layers, followed by transformation through a Gaussian-weighted feature tokenizer. Second, we introduce an enhanced bifurcation attention mechanism with dynamically adjustable perceptual ranges to capture spatial semantic information from both horizontal and vertical perspectives. Third, a convolutional multilayer perceptron module is employed to extract high-level feature representations in both spatial and spectral dimensions, which are then refined by a light self-Gaussian attention module. Finally, a linear layer is used to determine the sample labels. Experiments conducted on three publicly available hyperspectral datasets illustrate that the proposed DSNet achieves superior performance compared with several contemporary state-of-the-art methods, even when trained with limited samples. © 2025 Society of Photo-Optical Instrumentation Engineers (SPIE).

关键词： Convolutional neural networks

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On-orbit attitude planning for Earth observation imaging with star-based geometric calibration

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Science China(Technological Sciences) 2025年第2期68卷 243-256页

作者： Di HUANG Zhifu WANG Jianya GONG Haoran JI Institute of Aerospace Science and Technology School of Remote Sensing and Information EngineeringWuhan UniversityWuhan 430072China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingSchool of Remote Sensing and Information EngineeringWuhan UniversityWuhan 430072China National Key Laboratory of Air-based Information Perception and Fusion Luoyang 471009China Intelligent Game and Decision Laboratory Beijing 100071China

To improve the quality of remote sensing images,a novel on-orbit attitude planning method for Earth observation imaging with star-based geometric calibration is presented in this *** traditional imaging processes,the proposed method includes both pre-calibration and post-calibration stages to enhance the accuracy of satellite geometric positioning.A multiple-constraint attitude planning algorithm was developed to ensure star-based calibration,wherein the satellite camera and star sensors simultaneously capture the images of *** integration of cameras and multiple star sensors enables effective attitude *** the Earth imaging stage,a fast on-orbit attitude planning algorithm was developed to determine the satellite attitude and the optimal imaging times for ground *** with existing methods,the fast on-orbit attitude planning algorithm can significantly reduce computational time and resource consumption via initial value selection and *** demonstrate the effectiveness of the proposed attitude planning method,which was successfully applied to Wuhan 1 satellite.

关键词： attitude planning Earth observation imaging geometric calibration attitude constraints

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Facial micro-expression recognition based on dual-stream fusion network

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Multimedia Tools and Applications 2025年 1-14页

作者： Sun, Jiacheng Chen, Changhong Jiangsu Key Laboratory of Intelligent Information Processing and Communication Technology Nanjing University of Posts and Telecommunications No.66 Xin Mofan RD Nanjing210003 China

Micro-expressions(MEs) have emerged as a viable strategy for affective estimation due to their high reliability in emotion detection. In recent years, deep learning methods have been successfully applied to the field of micro-expression recognition. However, extracting and learning features from MEs presents challenges due to their brief duration and subtle intensity. To address these challenges, we propose the dual-stream fusion network (DSFNet). Specifically, we design shallow tokens-to-token vision transformers (T2T-ViT) to effectively capture comprehensive spatial position information. We also fine-tuned the number of ViT encoders and heads to enhance overall model performance. Additionally, the proposed multiscale convolution block (MCB) and attention mechanism modules (AMM) facilitate the effective extraction of detailed and valuable multiscale features from MEs. By employing various sizes of convolutional kernels and attention mechanisms, our approach captures higher-level image information, thereby improving MER accuracy. Finally, we integrate the information obtained from both branches. Performance evaluations on three mainstream ME datasets-SMIC, CASME II, and SAMM-demonstrate that the proposed framework significantly outperforms other advanced methods in micro-expression classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Deep learning

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Identification of Non-Restorative Sleep Associated with Depression Using Ambulatory Electrocardiogram and Triaxial Acceleration

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IEEE Transactions on Biomedical Engineering 2025年第6期72卷 1909-1919页

作者： Liu, Li Wang, Chongyang Liu, Guangyuan Wen, Wanhui Southwest University Chongqing Key Laboratory of Generic Technology and System of Service Robots Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China Sichuan University Key Laboratory of Rehabilitation Medicine in Sichuan Province Department of Rehabilitation Medicine Institute of Rehabilitation Medicine West China Hospital Chengdu610041 China

Objective: Non-restorative sleep is prevalent among individuals with depression and is strongly associated with the severity of the condition. Therefore, identifying non-restorative sleep can aid in the early screening of depression. Investigating non-restorative sleep in depression necessitates long-term monitoring under naturalistic conditions. Methods: In this study, we recruited 149 participants and collected electrocardiogram and triaxial acceleration from them, resulting in a total of 761 nights of data. The period from midnight to 6:30 AM was segmented into 78 five-minute intervals, from which 40 physiological features were extracted for each interval. To deal with variations in sleep patterns across participants and dates, we reordered the sleep data based on levels of parasympathetic nervous system (PNS) activation to explore the underlying neural mechanisms of non-restorative sleep in individuals with depressive symptoms. Results: We developed a model that integrated convolutional neural networks with an attention mechanism to identify nonrestorative sleep in individuals with depressive symptoms. The model demonstrated impressive performance on an independent test set, achieving an accuracy of 81.25% and an F1 score of 77.85%. Additionally, Bayes' theorem was used to compute the posterior probability indicating nonrestorative sleep in this population, assessing abnormal PNS activation. Conclusion: Finally, we designed a system capable of automatically evaluating nighttime sleep status and quantifying changes in non-restorative sleep associated with depression. Significance: This system offers a novel tool and method for the early identification of individuals at risk of depression. © 1964-2012 IEEE.

关键词： Sleep research

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