检索结果-内蒙古大学图书馆

High-Quality Reconstruction of Depth Maps From Graph-Based Non-Uniform Sampling

IEEE TRANSACTIONS ON MULTIMEDIA 2025年 27卷 780-791页

作者： Yang, Jingyu Xu, Wenqiang Hou, Yusen Ye, Xinchen Frossard, Pascal Li, Kun Tianjin Univ Sch Elect & Informat Engn Tianjin 300072 Peoples R China Dalian Univ Technol DUT RU Int Sch Informat Sci & Engn Dalian 116024 Peoples R China Ecole Polytech Fed Lausanne Signal Proc Lab CH-999034 Lausanne Switzerland Tianjin Univ Coll Intelligence & Comp Tianjin 300350 Peoples R China

Depth sensing is essential for intelligent computer vision applications, but it often suffers from low range precision and spatial resolution. To address this problem, we propose a novel framework that combines non-uniform sampling and reconstruction based on graph theory. Our framework consists of two main components: (1) a graph Laplacian induced non-uniform sampling (GLINUS) scheme that samples depth signals more densely around edges and contours than in smooth regions, and (2) an ensemble of priors (EoP) model that reconstructs the high-quality depth map using adaptive dual-tree discrete wavelet packets (ADDWP) transform, graph total variation regularizer, and graph Laplacian regularizer with color guidance. We solve the reconstruction problem using the alternating direction method of multipliers (ADMM). Our experiments demonstrate that our framework can capture fine structures and global information in depth signals and produce superior depth reconstruction results.

关键词： image reconstruction Laplace equations Spectral analysis Color Task analysis Filtering algorithms image color analysis Graph signal processing non-uniform sampling depth reconstruction

来源：评论

学校读者我要写书评

暂无评论

Application of High-Definition Imaging Technology in Traffic Violation Monitoring and Judicial Proceedings

引用

Traitement du signal 2025年第2期42卷 1007-1017页

作者： Hu, Zijun Li, Jia College of Humanities and Social Sciences Hebei Agricultural University Baoding071001 China

With the rapid growth of urbanization and the increasing number of motor vehicles, traffic violations have become more frequent, posing severe challenges to road safety and urban management. The application of high-definition (HD) imaging technology in traffic violation monitoring enables more accurate and efficient detection and processing of violations, significantly enhancing the intelligence level of traffic management and the effectiveness of judicial evidence collection. While existing research has made progress in developing and optimizing traffic violation monitoring systems, there remain significant shortcomings in multi-object tracking and the construction of judicial evidence chains. Current multi-object tracking algorithms are susceptible to occlusion and target loss in complex traffic environments, and existing judicial evidence chain construction methods heavily rely on single-image processing techniques, which limits the reliability and completeness of the evidence. This study focuses on two key aspects: (1) multi-object tracking in HD traffic violation monitoring images based on an improved DeepSORT algorithm and (2) judicial evidence chain construction using the Discrete wavelet Transform-Singular Value Decomposition (DWT-SVD) technique. The enhanced DeepSORT algorithm integrates deep learning with traditional tracking methods, significantly improving tracking accuracy and robustness in complex traffic conditions. Meanwhile, the DWT-SVD technique enables multi-level analysis and evidence extraction, strengthening the comprehensiveness and reliability of judicial evidence. This research not only advances the theoretical understanding of image processing in traffic violation monitoring and judicial applications but also provides valuable insights for practical implementation and broader adoption. ©2025 The authors.

关键词： image understanding

来源：评论

学校读者我要写书评

暂无评论

A Speech Enhancement Algorithm Combining wavelet Transform and Adaptive Filters 6

A Speech Enhancement Algorithm Combining Wavelet Transform a...

引用

6th IEEE International Conference on image processing, applications and Systems, IPAS 2025

作者： Shrestha, Aayam Ghorshi, Seyed Joorabchi, Marjan Panahi, Issa Firouzeh, Fereshteh Fakhar The University of Texas at Tyler Department of Electrical and Computer Engineering TX United States Sharif University of Technology School of Science and Engineering Iran The University of Texas at Dallas Department of Electrical and Computer Engineering TX United States

ISBN: (纸本)9798331506520

Noise as an unwanted interference can significantly degrade speech signals, especially those recorded by many microphones. This interference is modeled as additive noise that originates from a range of sources including White Gaussian Noise (WGN), babble, crowd, large city, and traffic noises. These disturbances can alter the characteristics of speech signals reducing both their quality and intelligibility. This paper introduces a novel approach designed to reduce noise and enhance the quality and intelligibility of speech signals. The proposed method combines wavelet Transform with Adaptive Filters, specifically the Wiener filter and RLS filter. The evaluation process involves testing noisy speech signals under realistic conditions with different signal-to-noise ratios (SNRs) and different types of additive noise. The objective measure is used for evaluation, including the perceptual evaluation of speech quality (PESQ). Results show that combining Wiener or RLS filtering with wavelet Transform significantly improves noise reduction, outperforming the use of wavelet Transform alone. © 2025 IEEE.

关键词： Adaptive filtering

来源：评论

学校读者我要写书评

暂无评论

Supervised single-channel dual domains speech enhancement technique using bidirectional long short-term memory

引用

Multimedia Tools and applications 2025年第5期84卷 2779-2803页

作者： Hosen, Md. Shakhawat Basir, Samiul Khan, Md. Farukuzzaman Asaduzzaman, A.O.M. Islam, Md. Mojahidul Islam, Md Shohidul Department of Computer Science and Engineering Islamic University Kushtia7003 Bangladesh Dhaka Bangladesh Hong Kong

This article introduces a brand new supervised method to make speech sound better and clearer by getting rid of background noise and mess-ups. It brings together two kinds of signal processes: the dual-tree complex wavelet transform (DTCWT) along with the short-time Fourier transform (STFT), in addition to a bidirectional long short-term memory (BLSTM) network. By taking the features from both time-frequency and wavelet domains, this way deals with issues of the discrete wavelet transform (DWT), like dealing with big changes and getting the direction right. The DTCWT makes subband signals that then change into a complex spectrogram using STFT. The size of this spectrogram is put into a bunch of layers in the BLSTM network, which finds speech bits well by knowing what came before and what’s coming next in data sequences. Soft mask parts are used to tweak this procedure. Matrix multiplication is implemented between the noisy complex spectrogram and the predicted mask of the model to produce the enhanced matrix. The final speech parts are made using inverse STFT and inverse DTCWT with the original parameters. How well this way works is tested against different kinds of noise, like stationary, quasi-stationary, and non-stationary, using both the IEEE Corpus and Aurora-2 databases. Results prove it gets a PESQ score of 3.34 and an STOI score of 0.918 at 0 signal-to-noise ratio (SNR) and also performs better for others. Other ways to gauge how good it is, like HASQI and HASPI, also do better than other methods, showing off better voice quality and understandability in different noisy spots. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

Multi-image encryption based on three-step phase-shifting digital holography

引用

JOURNAL OF OPTICS-INDIA 2025年 1-13页

作者： Li, Fei Fang, Hui Jing, Hao Su, Yonggang Hebei Univ Coll Elect & Informat Engn Baoding 071000 Hebei Peoples R China

As a cutting-edge imaging technology that combines optical holography principles with digital signal processing, digital holography holds significant potential for applications in optical image encryption. However, current optical image encryption methods based on digital holography are predominantly designed for single images. With the rapid development of big data, the Internet, and modern communication technologies, single-image encryption methods have increasingly struggled to meet the growing demands for image data privacy protection. Furthermore, the robustness of most existing optical image encryption methods has not been sufficiently validated through communication experiments. Therefore, this paper proposes a multi-image encryption scheme based on three-step phase-shifting digital holography. In this proposed scheme, a chaotic system is used to generate random phase mask keys during the encryption and decryption processes. This not only enhances the security of the encryption system but also simplifies the management and transmission of secret keys. By employing wavelet decomposition and reconstruction, this proposed scheme can simultaneously encrypt four grayscale images, thereby improving the efficiency of image encryption. Simulation results indicate that the proposed scheme offers high security, effectively resisting brute force attack. Additionally, orthogonal frequency division multiplexing (OFDM) communication experiments demonstrate that the proposed scheme is also highly robust.

关键词： Optical image encryption Three-step phase-shifting digital holography Chaotic random phase encoding OFDM communication system

来源：评论

学校读者我要写书评

暂无评论

Heart signal processing Using wavelet Analysis and Deep Learning Algorithms Based on Artificial Intelligence

Heart Signal Processing Using Wavelet Analysis and Deep Lear...

引用

International Conference on applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2024

作者： Zilaie, Morteza Mohammadkhani, Zohreh Asrari, Keyvan Azimi Talebiyan, Seyed Reza Islamic Azad University Science and Research Branch Khorasan Razavi Mashhad Iran The University of Pavia Pavia Italy Imam Reza International University Khorasan Razavi Mashhad Iran

ISBN: (纸本)9783031840999

The electrocardiogram signal of the heart is used to monitor the health status and function of the human heart and to a doctor in diagnosing the type of disease. For this purpose, first, the scalogram of the different heart failures produces different types of this signal. In this research, the cardiac signals of the patients are analyzed by an artificial intelligence neural network, and the type of the person’s disease is diagnosed. The artificial intelligence in question can be learned and can be used as an assistant ECG signal is calculated using continuous wavelet transform and then it is subjected to learning and evaluation using a deep convolutional neural network. In the architecture of artificial intelligence, two well-known neural networks GoogLeNet and SqueezeNet are used, which have been sufficiently trained in similar applications such as image processing and machine vision. In the end, the type of heart failure is diagnosed and classified. The cardiac signals of the patients used in the simulation were extracted from the PhysioNet medical engineering standard dataset of MIT University. In the end, the simulation results of the research are given. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Enhancement of Coastline Video Monitoring System Using Structuring Element Morphological Operations

引用

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND applications 2025年第1期16卷 603-611页

作者： Pawana, I. Gusti Ngurah Agung Widyantara, I. Made Oka Sudarma, Made Wiharta, Dewa Made Jayantari, Made Widya Udayana Univ Elect Engn Dept Badung Indonesia Udayana Univ Civil Engn Dept Badung Indonesia

Coastal monitoring is vital in environmental management, disaster mitigation, and addressing climate change impacts. Traditional methods are time-consuming and error- prone, prompting the need for innovative systems. This study introduces the Coastal Video Monitoring System (CoViMos), a novel framework for real-time shoreline detection in tropical regions, specifically at Kedonganan Beach, Bali. The CoViMos framework utilizes advanced video monitoring and optimized morphological operations to address challenges such as environmental noise and dynamic shoreline behavior. Key innovations include Kapur's entropy thresholding enhanced with the Grasshopper Optimization Algorithm (GOA) and structuring elements tailored to the beach's unique features. Sensitivity analysis reveals that a structuring element size of five pixels offers optimal performance, balancing efficiency, and image fidelity. This configuration achieves peak values in quality metrics such as the Peak signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Complex wavelet SSIM (CWSSIM), and Feature Similarity Index (FSIM) while minimizing Mean Squared Error (MSE) and reducing processing time. The results demonstrate significant improvements in shoreline detection accuracy, with PSNR increasing by 9.3%, SSIM by 1.4%, CWSSIM by 1.7%, and FSIM by 1.6%. processing time decreased by 1.3%, emphasizing the system's computational efficiency. These enhancements ensure more precise shoreline mapping, even in noisy and dynamic environments.

关键词： Coastline detection image processing Video Monitoring System (CoViMoS) morphological operations

来源：评论

学校读者我要写书评

暂无评论

Software design and FPGA implementation of optimized medical image fusion techniques

引用

Multimedia Tools and applications 2025年 1-31页

作者： Elshazly, E.A. El-Shafai, Walid El-Hoseny, Heba El-Rabaie, El-Sayed M Zahran, O. Abdelwahab, Safey A. S. El-Halawany, M.M. Fikry, R.M. Elaraby, S.M. Faragallah, Osama S. Mohamed, Wael A. Mahmoud, Korany R. Abd El-Samie, Fathi E. Cairo Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Faculty of Computer Studies Arab Open University 11681 Riyadh Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif University 11099 Taif21944 Saudi Arabia Department of Electrical Engineering Faculty of Engineering Benha University Benha Egypt Electronics and Communications Engineering Department Faculty of Engineering Helwan University Helwan Egypt Giza Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Nowadays, medical image fusion plays a crucial role in enhancing the diagnosis accuracy and the clinical decision-making process in various healthcare applications. This research work presents a comprehensive study of the design and implementation of optimized medical image fusion techniques using a combination of software and Field-Programmable Gate Array (FPGA) technologies. The proposed medical image fusion strategy is based on the utilization of Discrete wavelet Transform (DWT) and Modified Central Force Optimization (MCFO). The implementation of the proposed technique as well as the traditional medical image fusion techniques is considered using an appropriate software design and FPGA. The presented techniques aim to overcome the limitations of traditional fusion techniques by integrating advanced image processing algorithms, optimization algorithms, and parallel computing capabilities offered by FPGA platforms. The first step in the proposed framework is to match the histogram of one of the images with that of the other, so that both images will have the same dynamic range. After that, the DWT is used to decompose the images that should be fused together. Based on some constraints, the MCFO optimization algorithm is used to evaluate the optimum level of decomposition and the optimum parameters for the best fusion quality. Finally, to improve the obtained visual quality and reinforce the information in the fusion result, an additional contrast enhancement step using adaptive histogram equalization is applied to the fusion result. Comparative study between the proposed optimized DWT-based fusion framework, the traditional Principal Component Analysis (PCA), Additive wavelet Transform (AWT), and DWT-based fusion techniques is presented. Various metrics of fusion quality are considered, including average gradient, standard deviation, local contrast, entropy, edge strength, Peak signal-to-Noise Ratio (PSNR), Qab/f, and processing time. The proposed optimized DWT-ba

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Enhanced security framework for medical data embedding based on octonionic steganographic transforms and FPGA-accelerated integrity verification

引用

Alexandria Engineering Journal 2025年 125卷 480-495页

作者： Tahiri, Mohamed Amine Karmouni, Ilham Mchichou, Ismail Bencherqui, Ahmed El Maloufy, Ahmed Karmouni, Hicham Moustabchir, Hassane Sayyouri, Mhamed Khafaga, Doaa Sami Aldakheel, Eman Abdullah Abouhawwash, Mohamed Engineering Systems and Applications Laboratory National School of Applied Sciences Sidi Mohamed Ben Abdellah University Fez Morocco Laboratory of Electronic Signals and Systems of Information Sidi Mohamed Ben Abdellah University Fez Morocco National School of Applied Sciences Cadi Ayyad University Marrakech Morocco Department of Computer Sciences College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O.Box 84428 Riyadh11671 Saudi Arabia Department of Industrial and Systems Engineering King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia King Fahd University of Petroleum and Minerals Dhahran31261 Saudi Arabia

This study suggests a novel approach that combines steganography with innovative image and signal processing techniques to enhance the security and integrity of medical images. We employ octonions, which offer a rich and high-fidelity representation, to encode two medical images. Racah orthogonal polynomials (DORPs), which extract distinctive visual properties and are thus perfect for data concealment, are added to this method to improve it further. We created a verification method utilizing the SHA-256 hashing technique to guarantee data integrity. To identify any manipulation, this method computes the steganographic image's hash both before and after transmission. We used an FPGA-based technology to improve this process, which uses parallel processing to greatly speed up hash computations compared to conventional software techniques. Discrete wavelet decomposition (DWT), quaternion singular value decomposition (QSVD) of the cover picture, and the application of octonionic transforms to concealed images are the main components of our approach. Experimental results demonstrate high-fidelity image reconstruction, with PSNR values up to 40 dB, SSIM scores reaching 0.9900, and strong robustness against various attacks. In particular, the system achieves NC ≥ 0.98 even under geometric transformations such as rotation and scaling, thanks to an integrated geometric correction module based on the Arithmetic Optimization Algorithm (AOA). The FPGA implementation ensures low-latency integrity verification, making the framework suitable for embedded healthcare environments. The proposed solution shows strong potential for protecting sensitive diagnostic data in medical systems, combining mathematical rigor with hardware-level performance. © 2025

关键词： wavelet decomposition

来源：评论

学校读者我要写书评

暂无评论

wavelet-based Filtering of Noisy images by Amplification of Low-Frequency Components in High-Frequency Subbands

Wavelet-based Filtering of Noisy Images by Amplification of ...

引用

Digital signal processing and its applications (DSPA), International Conference on

作者： Y. S. Bekhtin V. T. Trinh Department of Automatics and Information Technologies in Control Ryazan State Radio Engineering University named after V.F. Utkin Ryazan Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

The paper describes a new method of noisy image restoration based on amplification of low-frequency components in high-frequency subbands, or details of fast wavelet transform (FWT). It makes a difference with respect to well-known wavelet filtering methods which are typically based on soft thresholding of wavelet coefficients belonging to high-frequency subbands of a noisy image. At the same time, the low-frequency component, or approximation can be used to extract the low-frequency components corresponding the details. It allows modifying the details of the FWT by adding the extracted low-frequency components that leads to increasing the signal-to-noise ratios in subbands. The paper contains the experimental results of modeling proving the effectiveness of the suggested method comparing to some widely used filtering methods, too. The results of modeling have shown that the proposed method allows improving quality of restored image by increasing both the signal-to-noise ratio and significantly reducing the number of ringing artifacts.

关键词： Wiener filters Filtering image edge detection Digital signal processing image restoration Noise measurement signal to noise ratio wavelet coefficients

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：