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Proceedings Paper

Evaluation of CPU and GPU architectures for spectral image analysis algorithms
Author(s): Virginie Fresse; Dominique Houzet; Christophe Gravier
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Paper 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 to 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.

Paper Details

Date Published: 25 January 2011
PDF: 11 pages
Proc. SPIE 7872, Parallel Processing for Imaging Applications, 78720M (25 January 2011); doi: 10.1117/12.872514
Show Author Affiliations
Virginie Fresse, Univ. de Lyon (France)
CNRS, Lab. Hubert Curien (France)
Univ. de Saint-Etienne, Jean-Monnet (France)
Dominique Houzet, GIPSA Lab. (France)
Christophe Gravier, Univ. de Lyon (France)
Univ. de Saint-Etienne, Jean-Monnet (France)
TELECOM Saint-Etienne (France)


Published in SPIE Proceedings Vol. 7872:
Parallel Processing for Imaging Applications
John D. Owens; I-Jong Lin; Yu-Jin Zhang; Giordano B. Beretta, Editor(s)

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