GPU-based accelerated processing of atmospheric hyperspectral remote sensing data

doi:10.13878/j.cnki.jnuist.2022.02.014

2025-5-29- 12

Home > Archive>Volume 14, Issue 2, 2022 >247-252. DOI:10.13878/j.cnki.jnuist.2022.02.014

GPU-based accelerated processing of atmospheric hyperspectral remote sensing data
DOI:
                        10.13878/j.cnki.jnuist.2022.02.014
                    
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                        ZHANG YuanZHANG Yuan
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093;Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 20008;Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083
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ZHANG DaweiZHANG Dawei
School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093
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CHEN RenCHEN Ren
Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 20008;Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083
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HUA JianwenHUA Jianwen
Shanghai Institute of Technical Physics, Chinese Academy of Sciences, Shanghai 20008;Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences, Shanghai 200083
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Abstract:

The demand for higher temporal and spatial resolution of atmospheric detection has brought about rapid increase of atmospheric hyperspectral remote sensing data;however,traditional methods have low efficiency for hyperspectral data processing.Here,we summarize the application examples of using GPU to accelerate the processing of hyperspectral remote sensing data,among which we focus on the parallel computing of the Fourier analysis of hyperspectral data based on the CPU-GPU heterogeneous mode.Then the CPU-GPU heterogeneous mode based parallel computing is implemented and then compared with traditional CPU-based computing.The results show that the data processing speed is increased by about 90 times while ensuring the data accuracy as well,thus verify the effectiveness of GPU to accelerate the processing of atmospheric remote sensing hyperspectral data.

Key words:hyperspectral remote sensing;graphics processing unit (GPU);high performance computing

Reference

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ZHANG Yuan, ZHANG Dawei, CHEN Ren, HUA Jianwen. GPU-based accelerated processing of atmospheric hyperspectral remote sensing data[J]. Journal of Nanjing University of Information Science & Technology,2022,14(2):247-252

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Received:May 22,2021
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Online: April 27,2022
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