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Proceedings Paper

GPUs for parallel on-board hyperspectral image radiometric normalization
Author(s): Yuanfeng Wu; Bing Zhang; Haina Zhao; Jianwei Gao; Li Ni; Wei Yang
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Paper Abstract

This paper proposed a GPU-based implementation of radiometric normalization algorithms, which is used as a representative case study of on-board data processing techniques for hyperspectral image. Three algorithms of radiometric normalization based on the column average and standard deviation of raw image statistical characteristics were implemented and applied to real hyperspectral images for evaluating their performance. These algorithms have been implemented using the compute device unified architecture (CUDA), and tested on the NVidia Tesla C2075 architecture. The airborne Pushbroom Hyperspectral Imager (PHI) was flown to acquire the spectrally contiguous images as experimental datasets. The results show that MN worked best among the three methods and the speedups achieved by the GPU implementation over their CPU counterparts are outstanding.

Paper Details

Date Published: 18 May 2013
PDF: 8 pages
Proc. SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 874322 (18 May 2013); doi: 10.1117/12.2015561
Show Author Affiliations
Yuanfeng Wu, Ctr. for Earth Observation and Digital Earth (China)
Bing Zhang, Ctr. for Earth Observation and Digital Earth (China)
Haina Zhao, Ctr. for Earth Observation and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Jianwei Gao, Ctr. for Earth Observation and Digital Earth (China)
Univ. of the Chinese Academy of Sciences (China)
Li Ni, Ctr. for Earth Observation and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Wei Yang, Ctr. for Earth Observation and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)


Published in SPIE Proceedings Vol. 8743:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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