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Unmixing-based content retrieval system for remotely sensed hyperspectral imagery on GPUs

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Abstract

This paper presents a new unmixing-based retrieval system for remotely sensed hyperspectral imagery. The need for this kind of system is justified by the exponential growth in the volume and number of remotely sensed data sets from the surface of the Earth. This is particularly the case for hyperspectral images, which comprise hundreds of spectral bands at different (almost contiguous) wavelength channels. To deal with the high computational cost of extracting the spectral information needed to catalog new hyperspectral images in our system, we resort to efficient implementations of spectral unmixing algorithms on commodity graphics processing units (GPUs). Spectral unmixing is a very popular approach for interpreting hyperspectral data with sub-pixel precision. This paper particularly focuses on the design of the proposed framework as a web service, as well as on the efficient implementation of the system on GPUs. In addition, we present a comparison of spectral unmixing algorithms available in the system on both CPU and GPU architectures.

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Notes

  1. http://symfony.com.

  2. http://www.w3.org/Protocols/rfc2616/rfc2616.html.

  3. http://www.ietf.org/rfc/rfc4251.txt.

  4. http://www.w3.org/Protocols/rfc959/.

  5. http://www.json.org/.

  6. http://jquery.com.

  7. http://www.w3.org/TR/html51.

  8. http://www.w3.org/Style/CSS.

  9. http://www.mysql.com.

  10. http://speclab.cr.usgs.gov.

  11. http://www.nvidia.es/object/tesla_c1060_es.html.

  12. http://www.bull.com/catalogue/details.asp?tmp=bxs-rack-fr&opt=ns-r422e02&dt=ft&cat=bullx.

  13. http://www.bull.com/catalogue/details.asp?tmp=bxs-node&opt=bullx-s6030e00&cat=bullx&dt=ft.

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Acknowledgments

This work was supported by the project AYA2011-29334-C02-02. And also, this work was partially supported by the computing facilities of Extremadura Research for Advanced Technologies (CETA-CIEMAT), funded by the European Regional Development Fund (ERDF). The CETA-CIEMAT belongs to the Spanish Ministry of Science and Innovation. Last but not least, the authors would like to take this opportunity to gratefully thank the editors and the two anonymous reviewers for their outstanding comments and suggestions, which greatly helped us to improve the technical quality and presentation of our manuscript.

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Correspondence to Antonio Plaza.

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The system is available online at: http://www.hypercomp.es/repository.

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Sevilla, J., Bernabe, S. & Plaza, A. Unmixing-based content retrieval system for remotely sensed hyperspectral imagery on GPUs. J Supercomput 70, 588–599 (2014). https://doi.org/10.1007/s11227-014-1104-2

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