Fast Non-Iterative PCA Computation for Spectral Image Analysis Using GPU
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Formal Metadata
| Title |
Fast Non-Iterative PCA Computation for Spectral Image Analysis Using GPU
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| Title of Series | |
| Part Number |
42
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| Number of Parts |
43
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| Author |
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| 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. |
| Identifiers |
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| Publisher |
River Valley TV
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| Release Date |
2011
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| Language |
English
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| Production Place |
Joensuu, Finland
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Content Metadata
| Subject Area | |
| 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.
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| Keywords |
The 5th European Conference on Colour in Graphics, Imaging
Vision and the 12th International Symposium on Multispectral Colour Science
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