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Fast Non-Iterative PCA Computation for Spectral Image Analysis Using GPU

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Title Fast Non-Iterative PCA Computation for Spectral Image Analysis Using GPU
Title of Series The 5th European Conference on Colour in Graphics, Imaging, and Vision and the 12th International Symposium on Multispectral Colour Science (CGIV 2010/MCS'10)
Part Number 42
Number of Parts 43
Author Antikainen, Jukka
Hauta-Kasari, Markku
Jääskeläinen, Timo
Parkkinen, Jussi
License CC Attribution - NoDerivatives 2.0 UK: England & Wales:
You are free to use, copy, distribute and transmit the work or content in unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
DOI 10.5446/18264
Publisher River Valley TV
Release Date 2011
Language English
Production Place Joensuu, Finland

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Subject Area Computer Science
Abstract In this study, we implement a fast non-iterative Principal Component Analysis computation for spectral image analysis by utilizing Graphical Processing Unit GPU. PCA inner product computation efficiency between Central Processing Unit CPU and GPU was examined. Performance was tested by using spectral images with different dimensions and different PCA inner product image counts. It will be shown that the GPU implementation provides about seven times faster PCA computation than the optimized Difference to the commonly used scientific analysis software Matlab is even higher. When spectral image analysis is needed to make in real-time, CPU does not offer the necessary performance for larger spectral images. Therefore, powerful GPU implementation is needed.
Keywords The 5th European Conference on Colour in Graphics, Imaging
Vision and the 12th International Symposium on Multispectral Colour Science
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