期刊文献+

GPU用于高光谱数据高性能计算的应用实践与分析 被引量:1

VALIDATION AND ANALYSIS OF HIGH PERFORMANCE COMPUTATION ON HYPERSPECTRAL IMAGERY BASED ON GPU
下载PDF
导出
摘要 高光谱遥感数据具有波段多、数据量大、处理复杂等特点,基于GPU的高性能计算在遥感领域得到了快速发展,为高光谱数据的快速处理提供了硬件和技术条件。采用GPU对高光谱遥感数据常用的SAM、PPI等处理算法进行应用实验,验证基于GPU的高光谱遥感数据快速处理技术。实验采用新疆东天山地区的一景星载Hyperion数据,利用支持IDL开发语言的GPULib、CUDA运行时API库进行算法效率的验证,结果表明,基于GPU的高光谱数据处理效率比常规的多核CPU主机处理效率有较大提升,具有一定的应用推广价值。 Hyperspectral imagery has many characteristics,such as plenty of bands,large volume of data,high computing complexity. In recent years,high performance computation has been making great progress in remote sensing based on GPU,providing the hardware and technical conditions for the rapid processing of hyperspectral data. We implemented the experiments on a hyperspectral image which was obtained by Hyperion of EO-1 satellite in East Tianshan area,Xinjiang,using SAM and PPI algorithms based on CPU and GPU,trying to study the fast processing technology on hyperspectral data.. Actually the GPULib and CUDA API were used through IDL language and the data was tested by different algorithms. The results show that the processing efficiency of hyperspectral data in GPU is greater than CPU and the technology can be used in remote sensing image processing.
出处 《地质力学学报》 CSCD 北大核心 2015年第2期190-198,共9页 Journal of Geomechanics
基金 中国地质调查局地质调查项目"地质勘查遥感系统集成与综合应用示范"(1212011120226)
关键词 高光谱数据 GPU 高性能计算 SAM PPI hyperspectral data GPU high performance computation SAM PPI
  • 相关文献

参考文献14

  • 1王润生,甘甫平,闫柏琨,杨苏明,王青华.高光谱矿物填图技术与应用研究[J].国土资源遥感,2010,22(1):1-13. 被引量:93
  • 2王润生,熊盛青,聂洪峰,梁树能,齐泽荣,杨金中,闫柏琨,赵福岳,范景辉,童立强,林键,甘甫平,陈微,杨苏明,张瑞江,葛大庆,张晓坤,张振华,王品清,郭小方,李丽.遥感地质勘查技术与应用研究[J].地质学报,2011,85(11):1699-1743. 被引量:239
  • 3Gillis D, Bowles J H. Parallel implementation of the ORASIS algorithm for remote sensing data analysis [ C ] //Plaza A J Chang C I. High performance computing in remote sensing. US: Taylor & Francis Group, 2008.
  • 4Tihon J C. Parallel implementation of the recursive approximation of an unsupervised hierarchical segmentation algorithm [ C] // Plaza A J, Chang C L High performance computing in remote sensing. US: Taylor & Francis Group, 2008.
  • 5Wang Jianwei, Chang Chein-I. FPGA design for real-time implementation of constrained energy minimization for hyperspectral target detection [ C] //Plaza A J, Chang C I. High performance computing in remote sensing. US: Taylor & Francis Group, 2008.
  • 6Setoain J, Prieto M, Tenllado C, et al. Parallel morphological endmember extraction using commodity graphics hardware [J]. IEEE Geoscience and Remote Sensing Letters, 2007, 4 (3) : 441-445.
  • 7Agathos A, Li J, Petcu D, et al. Multi-GPU implementation of the minimum volume sirnplex analysis algorithm for hyperspectral unmixing [ J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014, 7 (6): 2281 -2296.
  • 8杨靖宇,张永生,董广军.基于GPU的遥感影像SAM分类算法并行化研究[J].测绘科学,2010,35(3):9-11. 被引量:11
  • 9罗耀华,郭科,赵仕波.基于GPU的高光谱遥感MNF并行方法研究[J].四川师范大学学报(自然科学版),2013,36(3):476-479. 被引量:6
  • 10宋义刚,叶舜,吴泽彬,韦志辉.基于GPU的高光谱遥感图像PPI并行优化[J].航天返回与遥感,2014,35(4):74-80. 被引量:4

二级参考文献162

共引文献330

同被引文献29

引证文献1

二级引证文献6

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部