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Solving reverse emergence with quantum PSO application to image processing

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Abstract

A quantum-inspired PSO (QPSO) algorithm for solving reverse emergence is proposed that is a hybridization of the particle swarm optimization (PSO) algorithm and quantum computing principles. For potential applications, we review specific image processing problems including image denoising and edge detection. Taking cellular automata as a modeling tool, an evolutionary process carried out by the QPSO algorithm attempts to extract the rules resulting in satisfactory image denoising and edge detection. Experimental results demonstrate the feasibility, the convergence and robustness of the QPSO algorithm for solving reverse emergence in the specific application of image processing.

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Authors and Affiliations

  1. Computer Science Department, Faculty of Sciences, University of Ferhat Abbas - Setif 1, Sétif, Algeria

    S. Djemame

  2. Computer Science Department, College of NTIC, Constantine 2 University, Constantine, Algeria

    M. Batouche

  3. LISSI Laboratory, Paris-Est Creteil University, Créteil, France

    H. Oulhadj & P. Siarry

Authors
  1. S. Djemame
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  2. M. Batouche
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  3. H. Oulhadj
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  4. P. Siarry
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Correspondence to P. Siarry.

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Communicated by V. Loia.

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Djemame, S., Batouche, M., Oulhadj, H. et al. Solving reverse emergence with quantum PSO application to image processing. Soft Comput 23, 6921–6935 (2019). https://doi.org/10.1007/s00500-018-3331-6

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  • DOI: https://doi.org/10.1007/s00500-018-3331-6

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