计算机工程2017，Vol.43Issue(5)：240-247,8.DOI:10.3969/j.issn.1000-3428.2017.05.039
异构计算平台图像边缘检测算法优化研究
Research on Image Edge Detection Algorithm Optimization on Heterogeneous Computing Platform
摘要
Abstract
With the increase of the size of the image data and the improvement of the image resolution,the performance of the image edge detection algorithm becomes the key to the real-time processing of the image.Based on the three aspects of quantitative acess memory,data localization and conditional branch optimization,this paper studies the GPU performance optimization of Canny edge detection algorithm on NVIDIA Tegra K1 heterogeneous computing platform combined with algorithm characteristics and underlying hardware architecture characteristics.The experimental results show that compared with the Canny edge detection algorithm based on OpenCV3.0 CPU,the optimized Canny edge detection algorithm achieves 13.2 times to 17.8 times performance acceleration ratio with different graphic data size,and has better detection performance.关键词
图像边缘检测/异构计算平台/向量化访存/数据本地化/条件分支优化Key words
image edge detection/heterogeneous computing platform/quantitative acess memory/data localization/conditional branch optimization分类
信息技术与安全科学引用本文复制引用
魏秋明,梁军,鲍泓,王晶,李论..异构计算平台图像边缘检测算法优化研究[J].计算机工程,2017,43(5):240-247,8.基金项目
国家自然科学基金(NSFC61271370) （NSFC61271370）
北京市教育委员会科技计划面上项目(SQKM201411417010,KM201311417001). （SQKM201411417010,KM201311417001）
