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25 October 2016 A new embedded solution of hyperspectral data processing platform: the embedded GPU computer
Lei Zhang, Jiao Bo Gao, Yu Hu, Ke Feng Sun, Ying Hui Wang, Juan Cheng, Dan Dan Sun, Yu Li
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Proceedings Volume 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology; 101560M (2016) https://doi.org/10.1117/12.2244966
Event: International Symposium on Optoelectronic Technology and Application 2016, 2016, Beijing, China
Abstract
During the research of hyper-spectral imaging spectrometer, how to process the huge amount of image data is a difficult problem for all researchers. The amount of image data is about the order of magnitude of several hundred megabytes per second. Traditional solution of the embedded hyper-spectral data processing platform such as DSP and FPGA has its own drawback. With the development of GPU, parallel computing on GPU is increasingly applied in large-scale data processing. In this paper, we propose a new embedded solution of hyper-spectral data processing platform which is based on the embedded GPU computer. We also give a detailed discussion of how to acquire and process hyper-spectral data in embedded GPU computer. We use C++ AMP technology to control GPU and schedule the parallel computing. Experimental results show that the speed of hyper-spectral data processing on embedded GPU computer is apparently faster than ordinary computer. Our research has significant meaning for the engineering application of hyper-spectral imaging spectrometer.
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Lei Zhang, Jiao Bo Gao, Yu Hu, Ke Feng Sun, Ying Hui Wang, Juan Cheng, Dan Dan Sun, and Yu Li "A new embedded solution of hyperspectral data processing platform: the embedded GPU computer", Proc. SPIE 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology, 101560M (25 October 2016); https://doi.org/10.1117/12.2244966
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KEYWORDS
Data processing
Parallel computing
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