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Halo reduction multi-exposure image fusion technique

Multimedia Tools and Applications 2025年第13期84卷 12347-12370页

作者： Sharif, Rizwan Amin, Benish Sukhia, Komal Nain Department of Electrical Engineering Institute of Space Technology Islamabad Pakistan Department of Computer Science Institute of Space Technology Islamabad Pakistan

Multi-exposure image fusion (MEF) involves combining images captured at different exposure levels to create a single, well-exposed fused image. MEF has a wide range of applications, including low light, low contrast, night photography, medical imaging, and remote sensing. However, MEF methods often face issues like artifacts, halos around edges, color inconsistencies, noise amplification, and difficulty in preserving fine details. Moreover, assessing the quality of fused images objectively is complex due to the subjective nature of human perception. Solving the challenges is essential to developing efficient MEF techniques that produce high-quality results across various scenarios. The proposed technique introduces an approach to handling halo artifacts and implementing MEF. The Dense Scale-Invariant Feature Transform (DSIFT) is used to capture vital information about image brightness, texture, and edges from source images. Three weight maps are computed from the local mean, signal strength, and the global gradient for initial weight estimation. The local mean represents the brightness of specific image areas, signal strength preserves essential details like textures and edges while reducing image noise, and global gradient helps identify regions with significant pixel value shifts across multiple exposure images. The weight maps are then combined using a weighted average and a Gaussian smoothing filter is applied to reduce inherent noise and discontinuities in the original weights. Subsequently, pyramid decomposition is performed to generate a fused image. The efficiency of the proposed method is extensively tested on challenging multi-exposure image sequences. The results of the proposed approach demonstrate its superiority in both subjective evaluation and objective metrics like the MEF-Structural Similarity Index (MEF-SSIM), Natural Image Quality Evaluator (NIQE) and Gradient based performance measure (QAB/f). © The Author(s), under exclusive licence to Springer

关键词： Image fusion

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A robust image encryption method based on block diagonal chaotic architecture with CNN performance evaluation metric

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Multimedia Tools and Applications 2025年 1-35页

作者： Mamandi, Vida Ardalani, Nahid Ghalamkari, Behbod Department of Electrical Engineering Central Tehran Branch Islamic Azad University Tehran Iran Department of Mechanical Electrical and Computer Engineering Science and Research Branch Islamic Azad University Tehran Iran

In this paper, a new block diagonal chaotic model (BDC) is investigated due to higher necessity of advanced secure data transmission method in wireless medium and considerable limitation on computational storage space. In this model, the image sparse coding using BDC matrix in noisy and Rayleigh fading channels is studied. The structured BDC model is designed with two schemes, including chaotic pseudo inverse matrix (CPI-m) and block diagonal chaotic structured matrix (BDC-m) using two chaotic maps, in which the initial values for generating nonlinear chaotic sequences are used as private key at the receiver side. The simulation results show that the retrieved data measured based on CPI and BDC schemes outperforms the chaotic compressive sensing (CCS) method over AWGN and Rayleigh fading channels by 6% and 22.7%, respectively. Also, the sensitivity of recovered BDC-based image increases to 10(−32) compared to that of 10(−16) for conventional CCS based image. Moreover, the encryption key space increases from 10(37) for standard CCS-based measurements to β×10111 for measured data based on the BDC model, which guarantees that the competitors access no information. Considering datasets from iterative reconstruction process, the image features are extracted using convolutional neural network (CNN) model by ResNet-18 and GoogleNet architectures. The improved performance of data based on CPI and BDC model is validated by retrieved images accuracy over the classifier support vector machine (SVM). © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2025.

关键词： Fading channels

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A Biasing Scheme for the Gain Compression Point Optimization of HBT Cascode D-Band LNAs

A Biasing Scheme for the Gain Compression Point Optimization...

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2024 IEEE BiCMOS and Compound Semiconductor Integrated Circuits and Technology Symposium, BCICTS 2024

作者： Serra, Lorenzo De Filippi, Guglielmo Piotto, Lorenzo Mazzanti, Andrea University of Pavia Department of Electrical Computer and Biomedical Engineering Italy

ISBN: (纸本)9798331541248

Cascode amplifiers with a matching network between the common-emitter (CE) and the common-base (CB) HBTs are popular in the sub-THz band for their enhanced gain. The stage is analyzed in this paper with focus on the large-signal behavior. It is first observed that the CE-CB interstage network can push the CB out of the linear class-A regime, limiting the input power at 1 dB gain compression. It is then shown that the issue can be avoided with a suitable biasing scheme, leading to enhanced dynamic range with superior power efficiency. The concept is applied to the design of a D-band LNA in BiCMOS technology. With a quiescent power consumption of 20 mW from 2 V supply, the LNA shows 17.5 dB gain and 5.5 dB NF at 170 GHz. The output-referred 1dB compression point is 4.2dBm with 9% power efficiency at 175 GHz. Compared to previously reported LNAs in the same band, measured results demonstrate a remarkable dynamic range improvement with the the highest power efficiency. © 2024 IEEE.

关键词： BiCMOS technology

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Discrete Current Controller for SPMSMs at Low Sampling-to-Fundamental Frequency Ratios Using Critical Damping Feedback

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IEEE Transactions on Power Electronics 2025年第8期40卷 11787-11798页

作者： Huang, Zhen Zhu, Rui Zhang, Yun Zanchetta, Pericle Nanchang University School of Information Engineering Nanchang330000 China Tianjin University School of Electrical and Information Engineering Tianjin300072 China University of Pavia Electrical Computer and Biomedical Engineering Department Pavia27100 Italy

The discrete current controllers can generally ensure high-performance machine control. However, for high-speed machines associated with low sampling-to-fundamental frequency ratios (SFR), the unavoidable disturbances will seriously affect the control performance. To address this issue, an advanced discrete current controller is proposed in this article. The critical damping feedback is used to achieve the maximum damping ratio of the disturbance loop at any SFR. Compared with the existing discrete controllers, the proposed one can significantly reduce the impact of multiple parameter mismatches on the performance of the controller while improving the current tracking response and enhancing the antidisturbance capability. Finally, the experimental results on a 10 krpm high-speed permanent magnet synchronous machine with the lowest SFR of 8 have proven the feasibility and advantages of the addressed current controller. © 1986-2012 IEEE.

关键词： Damping

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ComMatch: A semi-supervised learning classification algorithm based on model calibration

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Journal of Intelligent and Fuzzy Systems 2025年第6期48卷 811-822页

作者： Li, Ye Zhou, Jingkang School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China Department of Control Science and Engineering University of Shanghai for Science and Technology Shanghai China

Semi-supervised learning (SSL) aims to reduce reliance on labeled data. Achieving high performance often requires more complex algorithms, therefore, generic SSL algorithms are less effective when it comes to image classification tasks. In this study, we propose ComMatch, a simpler and more effective algorithm that combines negative learning, dynamic thresholding, and predictive stability discriminations into the consistency regularization approach. The introduction of negative learning is to help facilitate training by selecting negative pseudo-labels during stages when the network has low confidence. And ComMatch filters positive and negative pseudo-labels more accurately as training progresses by dynamic thresholds. Since high confidence does not always mean high accuracy due to network calibration issues, we also introduce network predictive stability, which filters out samples by comparing the standard deviation of the network output with a set threshold, thus largely reducing the influence of noise in the training process. ComMatch significantly outperforms existing algorithms over several datasets, especially when there is less labeled data available. For example, ComMatch achieves 1.82% and 3.6% error rate reduction over FlexMatch and FixMatch on CIFAR-10 with 40 labels respectively. And with 4000 labeled samples, ComMatch achieves 0.54% and 2.65% lower error rates than FixMatch and MixMatch, respectively. © 2025 – IOS Press. All rights reserved.

关键词： Semi-supervised learning

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Fast Routing With Rule Caching in Lossy Mobile SDN

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Journal of Institute of Control, Robotics and Systems 2023年第11期29卷 854-858页

作者： Kim, Janghan Park, Hyung-Seok Park, Kyung-Joon Department of Electrical Engineering and Computer Science DGIST Korea Republic of

Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) have been actively employed for tasks that are challenging for humans, such as scenarios like battlefield and disaster. Swarm unmanned systems, comprising UAVs and UGVs, experience dynamic additions or removals of unmanned aircraft. In this paper, we propose a rule caching-based recovery technique for achieving rapid forwarding rule establishment for additional UAVs deployed for recovery in wireless Software-defined Networking (SDN) based swarm unmanned systems. To validate the proposed algorithm, we conducted experiments by setting up a testbed using ODROID and a controller. Our results demonstrate that the proposed algorithm improves forwarding rule establishment performance by up to 50.3%. © ICROS 2023.

关键词： Ground vehicles

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Encryption of medical data based on blockchain and multi-chaotic maps

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Multimedia Tools and Applications 2025年第17期84卷 17871-17892页

作者： Sharma, Suvita Rani Singh, Birmohan Kaur, Manpreet Department of Computer Science and Engineering Sant Longowal Institute of Engineering and Technology Punjab Longowal148106 India Department of Electrical and Instrumentation Engineering Sant Longowal Institute of Engineering and Technology Punjab Longowal148106 India

In this work, the SHA-256 mapper of the blockchain has been utilized to secure medical data from brute-force attacks. The uniform distribution and lower correlation of the encrypted data are achieved using the multi-chaotic in the encryption approach. Also, the circular shift method is employed in the approach to avoid differential attacks. The encryption approach is applied to secure the patient information, medical signals (ECG and EEG), and medical images (Grayscale, RGB, and Hyperspectral). The performance of the proposed approach has been analyzed for twenty signals and fifty medical images. Performance metrics such as MSE, SNR, PSNR, entropy, histogram, variance, chi-square, NPCR, UACI, and SSIM have been considered to check the resilience of the proposed approach against various types of attacks. The proposed approach satisfies the requirements of performance metrics by achieving higher MSE values with lower SNR and PSNR values for the encrypted data. Furthermore, the proposed methodology attains an entropy approaching 8, signifying robust randomness and resistance against entropy attacks. The SSIM values for encrypted images are close to 0, indicating significant dissimilarity from the original images. The NPCR values surpassing 99.60% and UACI exceeding 33.40% demonstrate resilience against differential attacks in the proposed approach. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Cryptography

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CLASSIFICATION OF ROYAL DELICIOUS APPLES USING HYBRID FEATURE SELECTION AND FEATURE WEIGHTING METHOD BASED ON SVM CLASSIFIER

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Scalable Computing 2025年第2期26卷 940-949页

作者： Kaur, Sandeep Sachan, Manoj Kumar Aggarwal, Ashwani Kumar Department of Computer Science and Engineering Sant Longowal Institute of Engineering and Technology Punjab Longowal148106 India Department of Electrical and Instrumentation Engineering Sant Longowal Institute of Engineering and Technology Punjab Longowal148106 India

Fruit safety is a critical component of the global economy, particularly within the agricultural sector. There has been a recent surge in the incidence of diseases affecting fruits, leading to economic setbacks in agriculture worldwide. Conventional manual assessment methods are laborious, prompting the exploration of automated computerized techniques for evaluating fruit quality. This research presents a novel method for assessing the quality of golden delicious apples. A dataset comprising 1256 apple images was gathered under controlled conditions. Afterward Feature extraction focuses on texture features like LBP, GLCM, GLDM, DTF, and Gabor features, color features, and shape and size features. A total of 18654 features are extracted and normalized using z-score. A hybrid method for feature selection and weighting involves the mRMR algorithm to eliminate redundant features and the Sine Cosine Optimization Algorithm for feature weighting, enhancing classification performance. The SVM machine learning technique, augmented with optimized features, yielded a 10.53% improvement in accuracy compared to SVM alone. Validation against state-of-the-art methods using Friedman’s mean rank test underscored the statistical significance of this approach across various metrics. © 2025 SCPE.

关键词： Fruits

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Superior efficiency and stability of YbO_(x)-enhanced perovskite solar cells

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science China Materials 2024年第4期67卷 1356-1358页

作者： Qifeng Zhang Guozhong Cao Department of Electrical and Computer Engineering North Dakota State UniversityFargoND 58108-6050USA Department of Materials Science and Engineering University of WashingtonSeattleWA 98195-2120USA

Perovskite solar cells represent a revolutionary class of photovoltaic devices that have gained substantial attention for their exceptional performance and potential to provide an affordable and efficient solution for harnessing solar energy. These cells utilize perovskite-structured materials, typically hybrid organicinorganic lead halide compounds, as the light-absorbing layer.

关键词： energy perovskite stability

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Multilevel chaotic encryption model with cyclic redundancy check for medical data

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Neural Computing and Applications 2025年第5期37卷 3581-3603页

In telemedicine applications, it is crucial to ensure the authentication, confidentiality, and privacy of medical data due to its sensitive nature and the importance of the patient information it contains. Communication through open networks is insecure and has many vulnerabilities, making it susceptible to unauthorized access and misuse. Encryption models are used to secure medical data from unauthorized access. In this work, we propose a bit-level encryption model having three phases: preprocessing, confusion, and diffusion. This model is designed for different types of medical data including patient information, clinical data, medical signals, and images of different modalities. Also, the proposed model is effectively implemented for grayscale and color images with varying aspect ratios. Preprocessing has been applied based on the type of medical data. A random permutation has been used to scramble the data values to remove the correlation, and multilevel chaotic maps are fused with the cyclic redundancy check method. A circular shift is used in the diffusion phase to increase randomness and security, providing protection against potential attacks. The CRC method is further used at the receiver side for error detection. The performance efficiency of the proposed encryption model is proved in terms of histogram analysis, information entropy, correlation analysis, signal-to-noise ratio, peak signal-to-noise ratio, number of pixels changing rate, and unified average changing intensity. The proposed bit-level encryption model therefore achieves information entropy values ranging from 7.9669 to 8.000, which is close to the desired value of 8. Correlation coefficient values of the encrypted data approach to zero or are negative, indicating minimal correlation in encrypted data. Resistance against differential attacks is demonstrated by NPCR and UACI values exceeding 0.9960 and 0.3340, respectively. The key space of the proposed model is 1096, which is substantially mor

关键词： Telemedicine

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