GPU architecture evaluation for multispectral and hyperspectral image analysis

Abstract : Graphical Processing Units (GPU) architectures are massively used for resource-intensive computation. Initially dedicated to imaging, vision and graphics, these architectures serve nowadays a wide range of multi-purpose applications. The GPU structure, however, does not suit all applications. This can lead to performance shortage. Among several applications, the aim of this work is to analyze GPU structures for image analysis applications in multispectral to ultraspectral imaging. Algorithms used for the experiments are multispectral and hyperspectral imaging dedicated to art authentication. Such algorithms use a high number of spatial and spectral data, along with both a high number of memory accesses and a need for high storage capacity. Timing performances are compared with CPU architecture and a global analysis is made according to the algorithms and GPU architecture. This paper shows that GPU architectures are suitable to complex image analysis algorithm in multispectral.
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Conference papers
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https://hal-ujm.archives-ouvertes.fr/ujm-00531453
Contributor : Virginie Fresse <>
Submitted on : Tuesday, November 2, 2010 - 5:20:59 PM
Last modification on : Wednesday, July 25, 2018 - 2:05:30 PM

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  • HAL Id : ujm-00531453, version 1

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Virginie Fresse, Dominique Houzet, Christophe Gravier. GPU architecture evaluation for multispectral and hyperspectral image analysis. Conference on Design and Architectures for Signal and Image Processing (DASIP 2010), Oct 2010, Edinburgh, United Kingdom. 7 p. ⟨ujm-00531453⟩

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