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European Conference on Parallel Processing

Euro-Par 2011: Euro-Par 2011: Parallel Processing Workshops pp 502–510Cite as

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Peer Group and Fuzzy Metric to Remove Noise in Images Using Heterogeneous Computing

Peer Group and Fuzzy Metric to Remove Noise in Images Using Heterogeneous Computing

  • Ma. Guadalupe Sánchez30,
  • Vicente Vidal31 &
  • Jordi Bataller31 
  • Conference paper
  • 1329 Accesses

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7155)

Abstract

In this paper, we report a study on the parallelization of an algorithm for removing impulsive noise in images. The algorithm is based on the concept of peer group and fuzzy metric. We have developed implementations using Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) for Graphics Processing Unit (GPU). Many sequential algorithms have been proposed to remove noise, but their computational cost is excessive for real-time processing of large images. We developed implementations for a multi-core CPU, for a multi-GPU (several GPUs) and for a combination of both. These implementations were compared also with different sizes of the image in order to find out the settings with the best performance. A study is made using the shared memory and texture memory to minimize access time to data in GPU global memory. The result shows that when the image is distributed in multi-core and multi-GPU a greater number of Mpixels/second are processed.

Keywords

  • remove impulsive noise
  • peer group
  • fuzzy metric
  • parallel algorithm
  • CUDA
  • OpenMP
  • multi-core
  • multi-GPU

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References

  1. Smolka, B.: Peer group switching filter for impulse noise reduction in color images. Pattern Recognition Letters 31, 484–495 (2010)

    CrossRef  Google Scholar 

  2. Camarena, J.G., Gregori, V., Morillas, S., Sapena, A.: Fast detection and removal of impulsive noise using peer group and fuzzy metrics. Journal of Visual Communication and Image Representation 19, 20–29 (2008)

    CrossRef  Google Scholar 

  3. Toprak, A., Guller, I.: Impulse noise reduction in medical images with the use of switch mode fuzzy adaptive median filter. Digital Signal Processing 17(4), 711–723 (2007)

    CrossRef  Google Scholar 

  4. Schulte, S., Nachtegael, M., De Witte, V., Van der Weken, D., Kerre, E.E.: A Fuzzy Impulse Noise Detection and Reduction Method. IEEE Transaction on Image Processing 15, 5 (2006)

    Google Scholar 

  5. Shulte, S., Morillas, S., Gregori, V., Kerre, E.E.: A New Fuzzy Color Correlated Impulse Noise Reduction Method. IEEE Transaction on Image Processing 15, 10 (2007)

    Google Scholar 

  6. Shulte, S., De Witte, V., Nachtegael, M., Van der Weken, D., Kerre, E.E.: Fuzzy Two Step Filter for Impulse Noise Reduction From Color Images. IEEE Transaction on Image Processing 15, 11 (2006)

    Google Scholar 

  7. Shulte, S., De Witte, V., Nachtegael, M., Van der Weken, D., Kerre, E.E.: Fuzzy random impulse noise reduction method. Journal Fuzzy Sets and Systems 158(3) (2007)

    Google Scholar 

  8. Mélange, T., Nachtegael, M., Kerre, E.E.: Fuzzy Random Impulse Noise Removal From Colour Image Sequences: IEEE (2010)

    Google Scholar 

  9. Morillas, S., Gregori, V., Hervas, A.: Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images. IEEE Transaction on Image Processing 18, 7 (2009)

    CrossRef  MathSciNet  Google Scholar 

  10. Camarena, J.G., Gregori, V., Morillas, S., Sapena, A.: Some improvements for image filtering using peer group techniques. Image Vis. Comput. 28(1), 188–201 (2010)

    CrossRef  Google Scholar 

  11. Morillas, S., Gregori, V., Peris-Fajarnés, G.: Isolating impulsive noise pixels in color images by peer group techniques. Comput. Vis. Image Underst. 110(1), 102–116 (2008)

    CrossRef  Google Scholar 

  12. Camarena, J.G., Gregori, V., Morillas, S., Sapena, A.: Two-step fuzzy logic based method for impulse noise detection in colour images. Pattern Recognition Letters 31, 1842–1849 (2010)

    CrossRef  Google Scholar 

  13. Smolka, B.: Fast detection and impulsive noise remolval in color images. Real-Time Imaging 11, 389–402 (2005)

    CrossRef  Google Scholar 

  14. Sánchez, M.G., Vidal, V., Bataller, J., Arnal, J.: Implementing a GPU fuzzy filter for Impulsive Image Noise Correction. In: CMSSE (2010)

    Google Scholar 

  15. Kodak, http://r0k.us/graphics/kodak/index.html

  16. Nvidia, http://www.nvidia.es/page/home.html

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Author information

Authors and Affiliations

  1. Departamento de Sistemas y Computación, Instituto Tecnológico de Cd. Guzmán, 49100, Cd. Guzmán, Jalisco, Mexico

    Ma. Guadalupe Sánchez

  2. Departamento de Sistemas Informáticos y Computación E.P.S. Gandia, Universidad Politécnica de Valencia, 46730, Grao de Gandia, Valencia, Spain

    Vicente Vidal & Jordi Bataller

Authors
  1. Ma. Guadalupe Sánchez
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  2. Vicente Vidal
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  3. Jordi Bataller
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Editor information

Editors and Affiliations

  1. Scilytics, Koellnerhofgasse 3/15A, 1010, Vienna, Austria

    Michael Alexander

  2. ICAR-CNR, Via P. Castellino, 111, 80131, Napoli, Italy

    Pasqua D’Ambra

  3. University of Amsterdam, 1090, Amsterdam, Netherlands

    Adam Belloum

  4. Innovative Computing Laboratory, The University of Tennessee, USA

    George Bosilca

  5. Department of Experimental Medicine and Clinic, University Magna Græcia, 88100, Catanzaro, Italy

    Mario Cannataro

  6. Computer Science Department, University of Pisa, Italy

    Marco Danelutto

  7. Second University of Naples, Italy

    Beniamino Di Martino

  8. TU München, Boltzmannstr. 3, 85748, Garching, Germany

    Michael Gerndt

  9. Equipe Runtime, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Emmanuel Jeannot & Raymond Namyst & 

  10. Equipe HIEPACS, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Jean Roman

  11. Oak Ridge National Laboratory, Computer Science and Mathematics Division, 37831-6164, Oak Ridge, TN, USA

    Stephen L. Scott

  12. Department of Scientific Computing, University of Vienna, Nordbergstr. 15/3C, 1090, Vienna, Austrial

    Jesper Larsson Traff

  13. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831, Oak Ridge, TN, USA

    Geoffroy Vallée

  14. Technische Universität München, Germany

    Josef Weidendorfer

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Sánchez, M.G., Vidal, V., Bataller, J. (2012). Peer Group and Fuzzy Metric to Remove Noise in Images Using Heterogeneous Computing. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7155. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29737-3_55

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  • DOI: https://doi.org/10.1007/978-3-642-29737-3_55

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29736-6

  • Online ISBN: 978-3-642-29737-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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