Advertisement

A Fuzzy Metric in GPUs: Fast and Efficient Method for the Impulsive Image Noise Removal

  • María G. Sánchez
  • Vicente Vidal
  • Jordi Bataller
  • Josep Arnal
Conference paper

Abstract

The implementation of image correction algorithms on the CUDA platform is a relatively new field. Although the platform is easy to program, it is not easy to optimize the applications due to the number of decisions that have to be made. This paper reports an optimization study on the use of the CUDA platform to remove impulsive noise in images using fuzzy metric and the concept of peer group. The texture memory is used to speed up the access to data. In order to get the maximum bandwidth on the GPU memory, a strategy based on storing each pixel in 4 bytes is proposed.

Keywords

Noise removal in images Parallel systems GPU CUDA 

Notes

Acknowledgments

This work was funded by the Spanish Ministry of Science Innovation (Project TIN2008-06570-C04-04). María would also like to acknowledge DGEST-ITCG for the scholarship awarded through the PROMEP program (Mexico).

References

  1. 1.
    NVIDIA Programming guide version 2.3.1, http://www.nvidia.es/page/home.htmlGoogle Scholar
  2. 2.
    Ruiz, A., Ujaldón, M., et al.: The GPU on biomedical image processing for color and phenotype analysis. In: 7th IEEE International Conference on Bioinformatics and Bioengineering, pp. 1124–1128 (2007)Google Scholar
  3. 3.
    Yang, Z., Zhu, Y., Pu, Y.: Parallel image processing based on CUDA. In: International Conference on Computer Science and Software Engineering, pp. 198–201 (2008)Google Scholar
  4. 4.
    Morillas, S., Gregori, V. et al.: Local Self-Adaptive Fuzzy Filter For Impulsive Noise Removal in Color Images. Sci. Direct Signal Process. 88, 390–398 (2008)CrossRefMATHGoogle Scholar
  5. 5.
    Smolka, B., Chydzinski, A.: Fast detection and impulsive noise remolval in color images. Real-Time Imag. 11, 389–402 (2005)CrossRefGoogle Scholar
  6. 6.
    Camarena, J.G., Gregori, V., Morillas, S., Sapena, A.: Fast detection and removal of impulsive noise using peer group and fuzzy metrics. J. Vis. Commun. Image Represent. 19, 20–29 (2008)CrossRefGoogle Scholar
  7. 7.
    Gonzalez, R.C., Woods, R.E.: Digital image processing. Person Education, Upper Saddle River (2008)Google Scholar
  8. 8.
    Gutiérrez-Ríos, J., Brox, P., Fernández-Hernández, F., Baturone, I., Sánchez-Solano, S.: Fuzzy motion adaptive algorithm and its hardware implementation for video de-interlacing. Appl. Soft Comput. 11, 3311–3320 (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited  2011

Authors and Affiliations

  • María G. Sánchez
    • 1
  • Vicente Vidal
    • 2
  • Jordi Bataller
    • 2
  • Josep Arnal
    • 3
  1. 1.Departamento de Sistemas y ComputaciónInstituto Tecnológico de Cd. GuzmánCd. GuzmanMexico
  2. 2.Departamento de Sistemas Informáticos y Computación E.P.S. GandiaUniversidad Politécnica de ValenciaGrao de GandiaSpain
  3. 3.Departamento de Ciencia de la Computación e Inteligencia ArtificialUniversidad de AlicanteAlicanteSpain

Personalised recommendations