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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems XI"

共 16444 条记录，以下是1341-1350 订阅

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A Quality Evaluation Method for images in Adverse Weather Conditions

A Quality Evaluation Method for Images in Adverse Weather Co...

引用

Sensors, Electronics and Computer Engineering (ICSECE), IEEE International conference on

作者： Zhengxi Shao Jifeng Chen Wenxin Lin School of Information and Electromechanical Engineering Hunan International Economics University Changsha China

ISBN: (数字)9798350373646

ISBN: (纸本)9798350373653

By adopting an adaptive image quality evaluation method under adverse weather conditions, an advanced image defogging system has been developed. This system aims to predict the optimal algorithm for achieving the best image defogging results. The system integrates nine efficient defogging algorithms. To comprehensively evaluate the defogging performance of these algorithms, a set of evaluation metrics including PSNR, SSIM, LPIPS, ENL, MSE, and RMSE is employed to establish a comprehensive evaluation method. By calculating the values of these evaluation metrics, the optimal algorithm suitable for the image is predicted, and the defogged image produced by the optimal algorithm is processed to output the best-defogged image finally. All predicted data is stored in a database. When defogging an image, if there is matching data in the database, the corresponding optimal algorithm and image processing are directly selected, thereby enhancing the overall defogging efficiency.

关键词： Measurement image sensors image quality Adaptive systems Databases image processing Prediction algorithms Sensor systems Intelligent sensors Meteorology

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Asymmetric kernels for dead pixel replacement and cluster masking 33

Asymmetric kernels for dead pixel replacement and cluster ma...

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conference on Infrared Imaging systems - Design, Analysis, Modeling, and Testing XXxiII Part of SPIE Defense and Commercial Sensing conference

作者： Viljoen, Johan W. Goss, Tristan M. Hensoldt South Africa Pty Ltd Optron Div Nellmapius Dr ZA-0157 Irene South Africa

ISBN: (纸本)9781510650893;9781510650886

MWIR FPAs often contain a non-negligible number of dead pixels, and even clusters of pixels. In addition to the undesirable cosmetic effect that these flaws have on the output image, it can also be detrimental to downstream image exploitation efforts, including target detection and tracking algorithms. It is therefore necessary to mask such defects as early as possible, before it is exacerbated by the imaging pipeline processes, especially sharpening filters and contrast stretching, which are commonly used. This paper presents the results of an investigation into several dead-pixel replacement schemes of varying complexity, starting with simple replacement by the previous neighbor to interpolation using kernels of varying shapes and domain sizes. These are evaluated for accuracy, but also for their cluster-handling performance, latency impact, and suitability for real-time implementation on resource-constrained FPGA matrices. It is shown that asymmetric predictive kernels, optimized using neural nets or genetic algorithms, can offer significant improvements over naive last-good-neighbor replacement, while affording improved cluster-handling capability, low FPGA resource requirements, and incurring minimal and even zero latency.

关键词： dead pixel masking NUC image processing kernel integer math

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processing pipeline for automated data mining of the single astronomical objects from blurred CCD frames 12

Processing pipeline for automated data mining of the single ...

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12th International Scientific and Practical conference "Information Control systems and Technologies", ICST 2024

作者： Khlamov, Sergii Savanevych, Vadym Vlasenko, Vladimir Hadzhyiev, Emil Bondar, Yehor Netrebin, Yuriy Kharkiv National University of Radio Electronics Nauki avenue 14 Kharkiv61166 Ukraine National Space Facilities Control and Test Center Moskovska street 8 Kyiv01010 Ukraine INTTVE Limited O'Connell Bridge House D'Olier Street 2 DublinD02RR99 Ireland

In this paper the authors presented a sophisticated data mining pipeline, which was designed for restoring the high-quality images from the blurred frames made by the Charge-Coupled Device (CCD) cameras. The developed data mining pipeline leverages the modern informational technologies for the horizontal and vertical scalability. The core methodology integrates the following mathematical methods and algorithms: an inverse median filtration method for the noise reduction and the Lucy-Richardson algorithm for deblurring. The inverse median filtration effectively reduces impulsive noise while preserving edges, and the Lucy-Richardson algorithm iteratively refines the image by correcting for blurring effects encoded in the point spread function (PSF). The proposed system's architecture of the processing pipeline for automated data mining of the single astronomical objects from blurred CCD frames utilizes the following modern technologies: Python programming language, Redis, FastAPI, React, Docker, and Caddy to ensure high performance, scalability, and ease of deployment. This integrated approach significantly enhances the accuracy of astronomical observations, facilitating more precise studies of celestial objects. The proposed pipeline addresses the unique challenges of astronomical image processing, offering a robust solution for automated data mining of single astronomical objects. Our work demonstrates the potential to advance astronomical research by improving image clarity and reliability, contributing to various fields within astronomy. The combination of effective noise reduction and deblurring techniques, along with a scalable and high-performance system architecture, provides a comprehensive solution to the challenges faced in processing astronomical images. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Noise abatement

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Underwater Imaging Using Low Rank Matrix and Sparse Representation for Oil Pipeline Inspection

Underwater Imaging Using Low Rank Matrix and Sparse Represen...

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2023 7th International conference on Electrical, Mechanical and Computer Engineering (ICEMCE)

作者： Mingshuo Zhou Qizhi Zhang School of Electronic Engineering Xi’an Shiyou University Xi'an China

Due to the critical importance of underwater pipeline integrity, particularly in the oil and gas transportation sector. This paper addresses the significance of applying low-rank matrix and sparse representation theories in the context of underwater imaging, with a primary focus on oil pipeline inspection. By comparing the effects of three algorithms on image processing, the superiority of the Structured Low-Dimensional Representation (SLDR) algorithm is demonstrated. The research aims to enhance the accuracy and quality of underwater images, ensuring the safety and integrity of subaqueous pipeline systems.

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Dual-branch Approach for Tracking UAVs with the Infrared and Inverted Infrared image 7

Dual-branch Approach for Tracking UAVs with the Infrared and...

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7th International conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Li, Shaogang Gao, Jin Li, Liang Wang, Gang Wang, Yizheng Yang, xin University of South China Hengyang China Chinese Academy of Sciences Institute of Automation Beijing China Beijing Institute of Basic Medical Sciences Beijing China

ISBN: (纸本)9781665478571

The imaging for small unmanned aerial vehicles (UAVs) in infrared imaging systems is easily disturbed when they shuttle between different surrounding regions in a large background, resulting in target contrast inversion. Existing methods have poor tracking performance in this scenario. A dual-branch object tracking framework is proposed to tackle this problem. Firstly, the features of original and inverted infrared images are extracted by different branches. Then, a cross-correlation feature fusion module is proposed, which fuses the features of the two branches to enhance the features of the target area to obtain a more accurate bounding box regression. The proposed method achieves top performance compared with the existing state-of-the-art tracking algorithms, reaching the success rate of 78.39% and precision rate of 80.07% on the 2nd anti-UAV datasets, which are 5.84% and 4.52% higher than the SuperDiMP baseline. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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SigFeaDet: Signal Features-based UAV GPS Spoofing Detection using Machine Learning 29

SigFeaDet: Signal Features-based UAV GPS Spoofing Detection ...

引用

29th IEEE International conference on Parallel and Distributed systems, ICPADS 2023

作者： Wei, xiaomin Wang, Luyao Xidian University School of Cyber Engineering Xi'an China AVIC Aircraft Strength Research Institute of China Xi'an China

ISBN: (纸本)9798350330717

The GPS is the most common used satellite-based navigation and positioning system. It is an indispensable component for a UAV as it provides accurate location data that is critical for navigation and mission success. However, GPS spoofing attacks are becoming a growing threat to GPS-dependent systems. Most existing GPS spoofing detection methods for UAVs are proposed based on simulation data or depend on multiple UAVs. In this paper, we propose a signal feature-based GPS spoofing detection approach, SigFeaDet, for a UAV using machine learning techniques. Our basic idea is to use the anomalies of GPS signal features due to the discrepancy between normal and spoofing signals. The Carrier-to-Noise Density Ratio (CN0) and Doppler frequency are significant signal features for GPS satellite positioning, which can be applied to identify spoofing signals. Various machine learning algorithms are applied to train with normal and spoofing data to choose the best classifier. The open GPS dataset TEXBAT is processed to obtain signal data and we also perform flight experiments to collect GPS data to augment normal GPS signal dataset. The detection rate is more than 94.8% and the equal error rate (EER) is about 5%, and the detection period is only 0.4 second. © 2023 IEEE.

关键词： CN0 Doppler frequency GPS spoofing attack GPS spoofing detection UAV

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Development of GPU-based Parallel CFD Solver for Unstructured Meshes 7

Development of GPU-based Parallel CFD Solver for Unstructure...

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7th International conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2023

作者： Zhang, Ye Ren, Weijie Yu, Hang Li, Hua College of Aerospace Science and Engineering National University of Defense Technology Hunan Changsha410073 China

ISBN: (纸本)9798350382877

As computer technology and numerical algorithms rapidly develop, the role of computational fluid dynamics (CFD) in the fields of mechanical and aerospace engineering has become increasingly prominent. However, the outdated hardware level has hindered the application of CFD in both theory and engineering. In this article, we developed a CFD solver based on unstructured grids for compressible hypersonic flow. This solver achieved parallel computing based on GPUs using the CUDA programming model. We optimized the code to cater to the characteristics of CPU/GPU heterogeneous systems. The solver used a second-order finite volume method and an adaptive hybrid Riemann solver to accurately and robustly solve hypersonic flow problems. For grid sizes Up to tens of millions, the solver can achieve two orders of magnitude speedup. © 2023 IEEE.

关键词： Graphics processing unit

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Methodology for the empirical representation of image processing functions in EO/IR sensor system models and simulations 19

Methodology for the empirical representation of image proces...

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conference on Electro-Optical and Infrared systems - Technology and Applications xiX

作者： Hickman, Duncan L. Tektonex Ltd Argyll Rd Kilcreggan Argyll & Bute England

ISBN: (纸本)9781510655461

image processing design plays an important role in the overall performance of modern EO/IR cameras. Incorporating these functions into models and simulators presents a major design challenge, particularly for those cases where complex processing functions are required, such as those found in autonomous ATD/R systems. An established technique involves the use of image-based simulations which process pre- recorded imagery using representative image processing algorithms. However, such an approach requires extensive run times and a large volume of image data, both of which can be prohibitive. An alternative approach is presented here whereby a limited number of images are processed and then used to generate statistically based performance transfer functions utilising an appropriate interpolation scheme. These transfer functions are then used to represent the output response of the processing chain when the received imagery is subjected to different levels of degradations such as distortion and blurring. Such transfer functions can then be stored in multidimensional look-up tables which can be rapidly accessed by a system-level Monte Carlo performance simulation. The ability to represent and extract the performance-related transfer functions is dependent upon the image quality metrics, and the accuracy of the corresponding parametric model requires careful consideration of the model validation. An example simulation is presented based on an autonomous ATD/R sensor system mounted on an airborne platform. The importance of validation is demonstrated, and the increased run-time benefits are described. The proposed parametric image modelling approach provides sensor system designers with increased confidence in their design and compliance, and this helps reduces the early design risk.

关键词： image modelling empirical analysis parametric models image-flow models Monte Carlo simulations model validation ATR

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Adaptive threshold FAST corner detection algorithm combined with edge information

Adaptive threshold FAST corner detection algorithm combined ...

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2022 International conference on Optics and Machine Vision, ICOMV 2022

作者： Xu, Zeqian Zhao, Junyang Zhang, Zhili Yan, xinxu Xi'an Research Institute of Hi-Tech Shaanxi Gaoxin Xi'an710025 China

ISBN: (纸本)9781510653238

Corner detection is a method used to obtain image features in computer vision systems, and is widely used in motion detection, image matching, video tracking, three-dimensional modeling, and target recognition. Also called feature point detection. Aiming at the shortcomings of traditional fast corner point extraction algorithms that use fixed thresholds when extracting image feature points and are easily affected by illumination to extract external points on a smooth plane, this paper proposes an adaptive threshold FAST corner detection method combined with edge information. First, use the canny algorithm to extract the edge information of the image, and then explain the calculation method of the adaptive threshold, calculate the feature point extraction threshold according to the gray information of the image, and finally extract the FAST corner points from the edge information according to the adaptive threshold. The test results show that: compared with the original FAST corner detection algorithm, the improved algorithm has increased its running speed by more than 30%, and has significantly reduced the number of external points, and its noise resistance has also been significantly improved. © 2022 SPIE

关键词： Extraction

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An image defogging algorithm of a designed-FCMSPCNN for natural image 7

An image defogging algorithm of a designed-FCMSPCNN for natu...

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7th International conference on Intelligent Computing and Signal processing, ICSP 2022

作者： Li, xiaolong Lian, Jing Guo, Chenxi Chen, Yingying Lanzhou Jiaotong University School of Electronic and Information Engineering Lanzhou China Lanzhou University School of Information Science and Engineering Lanzhou China Anning Branch of China Telecom Co. Ltd Lanzhou China

ISBN: (纸本)9781665478571

In order to address the problem of defogging images of foggy scenes, this paper proposes a parameter-tunable image defogging algorithm based on the FC-MSPCNN model (DFC-MSPCNN). Firstly, the proposed model is used to defogger color fogging images. Secondly, we simple four key parameters and one synaptic weight matrix in the model, including α, β, V, Q and Wijkl, and how they are set. Thirdly, our proposed method for image defogging is derived from dark channel theory and retinex theory. Finally, our proposed model in image defogging aspect brings a good image defogging performance than other popular algorithms. © 2022 IEEE.

关键词： Parameter estimation

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