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Performance Analysis of MATLAB Parallel Computing Approaches to Implement Genetic Algorithm for Image Compression

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Intelligent Systems in Science and Information 2014 (SAI 2014)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 591))

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Abstract

This chapter presents how to use parallel computing approaches from MATLAB Parallel Computing Toolbox to implement genetic algorithm for fractal image compression. These approaches are: ParFor, CoDistributor and Parallel Cluster. This is done to decrease processing time as possible as and maintaining reconstructed image quality. Many experiments were executed with comparisons between the three approaches. The experimental results showed that decreasing the GA population size and increasing number of workers used for the three parallel computing approaches can reduce the compression time. Best results obtained from implementing parallel approaches with 6 workers and 150 population size. The execution speed reached 4, CR reached 90.97 % and PSNR reached 34.98 db. At the same time, best results obtained from Parallel Cluster approach and then from CoDistributor approach.

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Authors and Affiliations

  1. Faculty of Sciences and Information Technology, AL-Zaytoonah University of Jordan, P.O. Box 130, Amman, 11733, Jordan

    Omaima N. Ahmad AL-Allaf

Authors
  1. Omaima N. Ahmad AL-Allaf
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Correspondence to Omaima N. Ahmad AL-Allaf .

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Editors and Affiliations

  1. Graduate School of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information (SAI) Organization, London, United Kingdom

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, London, United Kingdom

    Rahul Bhatia

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AL-Allaf, O.N.A. (2015). Performance Analysis of MATLAB Parallel Computing Approaches to Implement Genetic Algorithm for Image Compression. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems in Science and Information 2014. SAI 2014. Studies in Computational Intelligence, vol 591. Springer, Cham. https://doi.org/10.1007/978-3-319-14654-6_25

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  • DOI: https://doi.org/10.1007/978-3-319-14654-6_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-14653-9

  • Online ISBN: 978-3-319-14654-6

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