VALIDATION AND ANALYSIS OF HIGH PERFORMANCE COMPUTATION ON HYPERSPECTRAL IMAGERY BASED ON GPU

XU Ning; XIAO Xin-yao; HU Yu-xin; WEN Jing; WANG Da-ming

Volume 21 Issue 2

Jun. 2015

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Article Navigation > Journal of Geomechanics > 2015 > 21(2): 190-198

XU Ning, XIAO Xin-yao, HU Yu-xin, et al., 2015. VALIDATION AND ANALYSIS OF HIGH PERFORMANCE COMPUTATION ON HYPERSPECTRAL IMAGERY BASED ON GPU. Journal of Geomechanics, 21 (2): 190-198.

Citation:

XU Ning, XIAO Xin-yao, HU Yu-xin, et al., 2015. VALIDATION AND ANALYSIS OF HIGH PERFORMANCE COMPUTATION ON HYPERSPECTRAL IMAGERY BASED ON GPU. Journal of Geomechanics, 21 (2): 190-198.

Citation:

XU Ning, XIAO Xin-yao, HU Yu-xin, et al., 2015. VALIDATION AND ANALYSIS OF HIGH PERFORMANCE COMPUTATION ON HYPERSPECTRAL IMAGERY BASED ON GPU. Journal of Geomechanics, 21 (2): 190-198.

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VALIDATION AND ANALYSIS OF HIGH PERFORMANCE COMPUTATION ON HYPERSPECTRAL IMAGERY BASED ON GPU

XU Ning^{1, 2, 3
,},
XIAO Xin-yao^{1, 2, 3},
HU Yu-xin^{1, 2},
WEN Jing⁴,
WANG Da-ming⁵

1.
Key Laboratory of Technology in Geo-spatial Information Processing and Application System, IECAS, Beijing 100190, China
2.
Institute of Electronics, Chinese Academy of Sciences, Beijing 100190, China
3.
University of Chinese Academy of Sciences, Beijing 100049, China
4.
China Aero Geophysical Survey and Remote Sensing Centre for Land and Resources, Beijing 100083, China
5.
Oil & Gas Survey, China Geological Survey, Beijing 100029, China

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Received: 2014-11-13
Published: 2015-06-01

Abstract

Abstract

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.
- hyperspectral data,
- GPU,
- high performance computation,
- SAM,
- PPI

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References(15)

References

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