Electromagnetic scattering and imaging simulation of extremely large-scale sea-ship scene based on GPU parallel technology

Aiming to solve the bottleneck problem of electromagnetic scattering simulation in the scenes of extremely large-scale seas and ships,a high-frequency method by using graphics processing unit(GPU)parallel acceleration technique is proposed.For the implementation of different electromagnetic methods of physical optics(PO),shooting and bouncing ray(SBR),and physical theory of diffraction(PTD),a parallel computing scheme based on the CPU-GPU parallel computing scheme is realized to balance computing tasks.Finally,a multi-GPU framework is further proposed to solve the computational difficulty caused by the massive number of ray tubes in the ray tracing process.By using the established simulation platform,signals of ships at different seas are simulated and their images are achieved as well.It is shown that the higher sea states degrade the averaged peak signal-to-noise ratio(PSNR)of radar image.

Parallel Image Processing: Taking Grayscale Conversion Using OpenMP as an Example

In recent years, the widespread adoption of parallel computing, especially in multi-core processors and high-performance computing environments, ushered in a new era of efficiency and speed. This trend was particularly noteworthy in the field of image processing, which witnessed significant advancements. This parallel computing project explored the field of parallel image processing, with a focus on the grayscale conversion of colorful images. Our approach involved integrating OpenMP into our framework for parallelization to execute a critical image processing task: grayscale conversion. By using OpenMP, we strategically enhanced the overall performance of the conversion process by distributing the workload across multiple threads. The primary objectives of our project revolved around optimizing computation time and improving overall efficiency, particularly in the task of grayscale conversion of colorful images. Utilizing OpenMP for concurrent processing across multiple cores significantly reduced execution times through the effective distribution of tasks among these cores. The speedup values for various image sizes highlighted the efficacy of parallel processing, especially for large images. However, a detailed examination revealed a potential decline in parallelization efficiency with an increasing number of cores. This underscored the importance of a carefully optimized parallelization strategy, considering factors like load balancing and minimizing communication overhead. Despite challenges, the overall scalability and efficiency achieved with parallel image processing underscored OpenMP’s effectiveness in accelerating image manipulation tasks.

The Symbiotic Relationship Unraveling the Interplay between Technology and Artificial Intelligence(An Intelligent Dynamic Relationship)

This article investigates the dynamic relationship between technology and AI(artificial intelligence)and the role that societal requirements play in pushing AI research and adoption.Technology has advanced dramatically throughout the years,providing the groundwork for the rise of AI.AI systems have achieved incredible feats in various disciplines thanks to advancements in computer power,data availability,and complex algorithms.On the other hand,society’s needs for efficiency,enhanced healthcare,environmental sustainability,and personalized experiences have worked as powerful accelerators for AI’s progress.This article digs into how technology empowers AI and how societal needs dictate its progress,emphasizing their symbiotic relationship.The findings underline the significance of responsible AI research,which considers both technological prowess and ethical issues,to ensure that AI continues to serve the greater good.

Application of Computer Vision Technology in Agriculture

With the development of image processing technology and computer, computer vision technology has been widely used in the production of agriculture,and has made many important achievements. This paper reviews its-research progress on diagnosis of agricultural products, water diagnosis, weed identification,product quality testing and grading, agricultural picking and sorting and other as- pects, and finally put forward its existing problems and prospects for the future.

Image processing algorithm acceleration using reconfigurable macro processor model

The concept and advantage of reconfigurable technology is introduced. A kind of processor architecture of re configurable macro processor (RMP) model based on FPGA array and DSP is put forward and has been implemented. Two image algorithms are developed: template-based automatic target recognition and zone labeling. One is estimating for motion direction in the infrared image background, another is line picking-up algorithm based on image zone labeling and phase grouping technique. It is a kind of 'hardware' function that can be called by the DSP in high-level algorithm. It is also a kind of hardware algorithm of the DSP. The results of experiments show the reconfigurable computing technology based on RMP is an ideal accelerating means to deal with the high-speed image processing tasks. High real time performance is obtained in our two applications on RMP.

Detection of Copy-Move Forgery in Digital Images Using Singular Value Decomposition

This paper presents an improved approach for detecting copy-move forgery based on singular value decomposition(SVD).It is a block-based method where the image is scanned from left to right and top to down by a sliding window with a determined size.At each step,the SVD is determined.First,the diagonal matrix’s maximum value(norm)is selected(representing the scaling factor for SVD and a fixed value for each set of matrix elements even when rotating thematrix or scaled).Then,the similar norms are grouped,and each leading group is separated into many subgroups(elements of each subgroup are neighbors)according to 8-adjacency(the subgroups for each leading group must be far from others by a specific distance).After that,a weight is assigned for each subgroup to classify the image as forgery or not.Finally,the F1 score of the proposed system is measured,reaching 99.1%.This approach is robust against rotation,scaling,noisy images,and illumination variation.It is compared with other similarmethods and presents very promised results.

Status and prospects of frozen soil studies using CT technology

This paper introduces the characteristics of Computed Tomography （CT） technology and reviews its history, current situation, representative achievements, and use of using CT technology on frozen soil study, including auxiliary equipment specially de- signed for frozen soil studies. CT numbers are used to analyze frozen soil internal structure change, defining and exploring dam- age evolution, and use of CT images on observing soil mesostructure. Finally, this paper presents existing problems confronted by using CT in frozen soil studies, possible solutions and challenges, among which, we introduce high quality CT image processing for frozen soils, and relations between CT number change and each component change on frozen soil samples within the region of interest. It is shown that present CT technology is one of the most ideal and effective technology to study frozen soil mesostructure using non-desmactive testing. CT technology will play a key role in the study and development in the field of frozen soil by means of auxiliary equipment and the digital imaging processing.

Graphic Processing Unit-Accelerated Mutual Information-Based 3D Image Rigid Registration

Mutual information （MI）-based image registration is effective in registering medical images, but it is computationally expensive. This paper accelerates MI-based image registration by dividing computation of mutual information into spatial transformation and histogram-based calculation, and performing 3D spatial transformation and trilinear interpolation on graphic processing unit （GPU）. The 3D floating image is downloaded to GPU as flat 3D texture, and then fetched and interpolated for each new voxel location in fragment shader. The transformed resuits are rendered to textures by using frame buffer object （FBO） extension, and then read to the main memory used for the remaining computation on CPU. Experimental results show that GPU-accelerated method can achieve speedup about an order of magnitude with better registration result compared with the software implementation on a single-core CPU.

基于机器视觉的飞机故障检查系统

针对当前飞机维修检查工作以人工目视检查为主、效率低且存在人为因素影响的情况,设计一套基于图像识别与机器深度学习的飞机部件表面无损检测系统。收集并整理了某航空公司一线飞机维修员拍摄的飞机机身及发动机部件图片,对图片集进行预处理,包括通道提取、Sobel滤波处理及二值化;最后用Blob分析对处理后的图像进行特征提取与系统分析。系统运行速度快、准确率高且可连续自动识别图像。利用机器视觉技术对飞机部件表面进行无损检测不仅可以提高生产效率,同时可以去除人为因素对航空器飞行安全的影响,使得飞机的飞行安全得到进一步提升。实践证明,该系统性能稳定可靠,具有极高的推广应用价值。

多光源照射下目标图像实时生成方法

由于地理位置、太阳、大气环境等因素限制,无法获取空间目标在各种姿态、光照条件、特别是激光、太阳和背景光共同作用下的实际成像。提出一种多光源照射下目标图像实时生成方法。该方法基于计算机图形学中纹理映射思想,采用现代图形显卡编程技术和帧缓存对象特性,在GPU(Graphics Processing Unit)端采用着色器语言实现多光源作用下目标亮度值高效计算和真实感增强;采用开源三维图形引擎OSG(Open SceneGraph)支持多种格式三维模型文件,提高与国产麒麟操作系统及常用战场态势显示软件的兼容性。仿真实验验证了该方法的有效性和优越性。

计算机图像处理技术在网页设计中的应用

运用文献研究法、综合分析法,在明确计算机图像处理技术概念及其相关技术类型基础上,阐述网页设计中计算机图像处理技术应用的优势,从网页类型与图像格式搭配设计等角度,提出几点如何发挥计算机图像处理技术在网页设计中应用优势作用的思路与策略.计算机图像处理技术多样性和图像组合优势可有效拓展网页设计思路,使其更加新颖且符合新时代下用户审美取向,从而促进网页的良好发展.

视频侦查技术关键及其发展展望

视频侦查技术的核心是通过视频图像的提取、查看、分析和研判来获取侦查线索、固定涉案证据。多年来经过在实战应用中不断地发展创新,视频侦查技术形成了自己独特的关键技术体系:视频信息分析解读技术是侦查应用和证据固定的基础和核心;视频证据固定保全技术的规范是审判中心主义的客观要求,可以获取视频侦查记录报告、视频检验鉴定报告或视频数据关联报告;低质量视频图像的增强恢复技术专业性强,应用范围窄,技术成熟度高,然而它不断面临新的挑战。目前,视频数据的智能应用在大数据背景下变得越来越重要,仍需进一步突破视频自动识别技术的应用范畴,建立完善多层次的视频数据综合应用体系,打造适应不同业务需要的视频数据实战应用模型。

背部痧象特征要素数显划分方法

目的通过对痧象图片数据的研究,提出一种数显的客观方法来对背部痧象特征要素进行准确辨识,以避免主观认知不同带来的偏差,帮助人们快速辨识痧象的相关特征,为中医医师的诊断提供一定的客观依据,减少主观化成分。方法首先,采用深度语义分割算法模型对采集的背部痧象图片进行分割,以获取只包含痧象的部分区域,去除图片中其他无关部分,尽可能减少对后续实验所带来的影响。然后针对分割得到的图像,结合中医五脏六腑在背部的映射区,采用关键区域检测的方法对痧象颜色特征进行3种区间的识别;根据中医主观上对于痧象形状的划分,采用像素统计方法将痧象形状划分为片状和点状两种。最后,通过准确度、精确度、召回率、F1值对客观识别的结果进行数据上的评价。结果本文提出的客观数显方法在痧象颜色特征划分上的准确率达到了80.56%,在痧象形状特征的划分上准确率达到了89.60%,能够较为准确地对痧象特征要素进行划分,具有一定的可行性。结论本文提出的数显方法能够对痧象的颜色和形状特征进行较为准确的辨识,可以在很大程度上避免主观认知所造成的辨识不同问题,在辅助医师诊断以及用于中医痧象特征的识别教学方面具有较大的应用前景,可为正确了解痧象特征信息提供帮助。

基于图形处理技术的文字符号商用研究

随着计算机技术的普及使用,图形处理技术在各行各业得到推广与应用,其中以互联网行业的应用最为广泛。图形处理技术在文字符号商业标志设计中的应用,不仅要平衡表现效果与艺术美感,还要从用户的角度思考,考虑如何提高商业标志的吸引力、改善用户的阅读感官体验。文字符号商业标志设计需要充分利用先进技术,将各种网络资源整合起来,提高信息传达与表现效果,从而提高商业标志的美感。图形处理技术的应用,主要是为了丰富商业标志内容、提高艺术美感,从而吸引更多的网民点击和浏览,改善网民的阅读体验。因此,需要重视图形处理技术的合理应用。

指针式仪表读数识别的研究现状与发展

在高温高压强磁场等恶劣环境下,指针式仪表有着优于数显式仪表的良好性能表现,对指针式仪表读数识别进行研究具有重要的现实意义。近年来,深度学习与计算机视觉紧密结合,基于深度学习的指针式仪表读数识别技术是前沿研究的重点方向。文中首先概述指针式仪表读数识别的过程,然后从3个方面论述指针式仪表读数识别技术的研究现状与进展:仪表图像的预处理、仪表表盘区域的检测和仪表的读数识别,论述过程中分别阐述基于传统机器学习的方法和基于深度学习的方法。最后介绍公开的仪表数据集和应用场景,并从深度学习算法、巡检机器人工作特点和公共数据集的建立3个方面对未来的研究进行展望与建议。

超厚纸张表面缺陷智能化图像处理与识别系统设计研究

设计一套智能化图像处理与识别系统,用于超厚纸张表面缺陷的检测,以解决传统超厚纸检测成本高、效率低、错误率高、精度低等问题。通过综合分析图像处理技术在超厚纸张表面缺陷检测中的可行性,从图像处理技术流程、应用可行性和系统设计等角度展开讨论,提出基于机器视觉的超厚纸张表面缺陷检测系统设计方案,包括整体设计、硬件环境和软件平台的选择与搭建,期望该系统能够高效、准确地检测超厚纸张表面的各类缺陷,提高超厚纸张生产质量和效率。

基于深度学习的农场虫情检测算法研究及实现

传统的病虫害防治手段需要消耗大量人力、物力,且达不到很高的精确度,为了更科学、高效地做好农场病虫害防治工作,本文结合深度学习技术和物联网技术研发了虫情检测系统进行病虫害的远程检测,提高防治工作的效率。该系统采用YOLO-v5网络模型,结合迁移学习,训练学习了林业常见害虫和农田常见害虫的特征,实现了高效的检测识别。基于物联网技术实现远程控制拍摄病虫害图像,并通过Wi-Fi传输到计算机端进行识别,通过可视化界面呈现出农田中虫害的种类和数量,对减少人力、物力消耗以及实现科学防虫具有良好的实际应用价值。

基于无人机PPK技术在免像控条件下山区光伏地形图的生产

针对光伏场区高差大、部分区域植被覆盖、通信信号弱的特点,本文提出了一种基于动态后处理技术(PPK)在免像控条件下航测光伏地形图生产的方法。该方法首先在免像控的条件下对航测获取的无人机影像定位测姿系统(POS)数据和点云数据进行PPK解算;然后利用点云后处理、影像空中三角测量、数字微分纠正等技术生成高精度数字高程模型(DEM)和数字正射影像(DOM)成果;最后利用DEM和DOM成果构建三维模型,实现地形图生产。利用两个典型应用实例,验证了该方法可完全满足光伏地形图的精度要求。

计算机技术在图形图像处理中的应用研究

计算机技术的发展在各个领域都带来了深远的影响,特别是在图形图像处理方面。它通过高效的算法和强大的计算能力,不仅提高了图形图像处理的速度和质量,还扩展了应用范围。本文从图形图像处理的基本概念出发,分析了计算机技术在图形图像识别、复原和增强、编辑与操作等方面的应用,为相关领域的研究和实践提供参考。

信息化时代“图像处理技术”课程建设与实践

文章针对信息化背景下学习活动模块化、时间碎片化和普通高等教育电子信息类专业课教学的自身特性,利用一体化平台整合教学资源,开展线上线下双线教学,同时实现教学全过程动态管理和成绩评价指标的量化记录;根据“图像处理技术”课程实践性强、应用广泛的特点,结合科研工程案例,利用平台开展翻转课堂形式的教学活动,并在教学过程中融入思政元素,激发学生学习积极性,增强学生的法律意识和科技强国的责任感;同时完善课程考核体系,提高课程参与度,取得了一定的实践效果。