并行计算在动态摄影测量边缘提取算法中应用  

Application of parallel computing in edge extraction algorithm in dynamic photogrammetry

作　　者：刘振涛[1] 燕必希[1] 董明利[1] 孙鹏[1,2] 王君[1] LIU Zhen-tao;YAN Bi-xi;DONG Ming-li;SUN Peng;WANG Jun(School of Instrument Science and Opto Electronics Engineering,Beijing Information Science and Technology University,Beijing 100192,China;Institute of Information Photonics and Optical Communications,Beijing University of Posts and Telecommunications,Beijing 100876,China)

机构地区：[1]北京信息科技大学仪器科学与光电工程学院,北京100192 [2]北京邮电大学信息光子学与光通讯研究院,北京100876

出　　处：《计算机工程与设计》2019年第1期97-102,共6页Computer Engineering and Design

基　　金：国家自然科学基金项目(51475046)

摘　　要：为满足动态摄影测量速度需求,设计一种将Hyper-Q技术应用于双站位相机图像Canny边缘提取算法中的实现方案。通过两个流对采集到的两幅图像分别处理,充分利用GPU计算资源,实现高效并行计算。对300个特征点3种不同分辨率图像进行特征点的Canny边缘检测,实验结果表明,在同样分辨率图像下,基于CUDA的边缘检测算法计算比串行计算算法速度提高了8.8倍,应用Hyper-Q技术后的CUDA程序比串行计算速度提高了11.6倍,图像处理速度显著提高,为双相机动态摄影测量系统在分辨率为4288×2848下实现3Hz测量速度提供思路。To meet the requirement of operating speed in dynamic photogrammetry,a method of CUDA and Hyper-Q technology was applied to Canny edge extraction of the dual-station camera images.Two image collected through two streams were processed separately,which made full use of GPU computing resources to realize the parallel computing.Canny edge extraction of 300 featured points in three different resolution images was implemented in experiment,the results show that the speed of edge detection algorithm based on CUDA is 8.8 times higher than the serial computation accessing the same image resolution,furthermore,the program applied Hyper-Q is 11.6 times higher compared with the serial computation,and so the image processing speed is significantly improved,which provides method for achieving 3 Hz measurement speed under the resolution of 4288×2848 using the dynamic photogrammetry system with dual camera.

关 键 词：动态摄影测量 并行计算 统一计算设备架构 Hyper-Q 边缘提取 

分 类 号：TP311.11[自动化与计算机技术—计算机软件与理论]