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Volume: 5 | Article ID: art00086
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Fast Non-Iterative PCA computation for spectral image analysis using GPU
  DOI :  10.2352/CGIV.2010.5.1.art00086  Published OnlineJanuary 2010
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 CPU version. Difference to the commonly used scientific analysis software Matlab is even higher. When spectral image analysis is needed to make in realtime, CPU does not offer the necessary performance for larger spectral images. Therefore, powerful GPU implementation is needed.

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Jukka Antikainen, Markku Hauta-Kasari, Timo Jaaskelainen, Jussi Parkkinen, "Fast Non-Iterative PCA computation for spectral image analysis using GPUin Proc. IS&T CGIV 2010/MCS'10 5th European Conf. on Colour in Graphics, Imaging, and Vision 12th Int'l Symp. on Multispectral Colour Science,  2010,  pp 554 - 559,  https://doi.org/10.2352/CGIV.2010.5.1.art00086

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Copyright © Society for Imaging Science and Technology 2010
72010351
Conference on Colour in Graphics, Imaging, and Vision
conf colour graph imag vis
2158-6330
Society of Imaging Science and Technology
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