Evaluation of CPU and GPU architectures for spectral image analysis algorithms

Virginie Fresse; Dominique Houzet; Christophe Gravier

doi:10.1117/12.872514

25 January 2011 Evaluation of CPU and GPU architectures for spectral image analysis algorithms

Virginie Fresse, Dominique Houzet, Christophe Gravier

Proceedings Volume 7872, Parallel Processing for Imaging Applications; 78720M (2011) https://doi.org/10.1117/12.872514
Event: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, United States

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.

Citation Download Citation

Virginie Fresse, Dominique Houzet, and Christophe Gravier "Evaluation of CPU and GPU architectures for spectral image analysis algorithms", Proc. SPIE 7872, Parallel Processing for Imaging Applications, 78720M (25 January 2011); https://doi.org/10.1117/12.872514

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