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Proceedings Paper

Further optimizations of the GPU-based pixel purity index algorithm for hyperspectral unmixing
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Paper Abstract

Many algorithms have been proposed to automatically find spectral endmembers in hyperspectral data sets. Perhaps one of the most popular ones is the pixel purity index (PPI), available in the ENVI software from Exelis Visual Information Solutions. Although the algorithm has been widely used in the spectral unmixing community, it is highly time consuming as its precision increases asymptotically. Due to its high computational complexity, the PPI algorithm has been recently implemented in several high performance computing architectures including commodity clusters, heterogeneous and distributed systems, field programmable gate arrays (FPGAs) and graphics processing units (GPUs). In this letter, we present an improved GPU implementation of the PPI algorithm which provides real-time performance for the first time in the literature.

Paper Details

Date Published: 8 November 2012
PDF: 6 pages
Proc. SPIE 8539, High-Performance Computing in Remote Sensing II, 85390D (8 November 2012); doi: 10.1117/12.979310
Show Author Affiliations
Xianyun Wu, Xidian Univ. (China)
Bormin Huang, Univ. of Wisconsin-Madison (United States)
Antonio Plaza, Univ. de Extremadura (Spain)
Yunsong Li, Xidian Univ. (China)
Chengke Wu, Xidian Univ. (China)

Published in SPIE Proceedings Vol. 8539:
High-Performance Computing in Remote Sensing II
Bormin Huang; Antonio J. Plaza, Editor(s)

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