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Low-Level Image Processing Based on Interval-Valued Fuzzy Sets and Scale-Space Smoothing

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Recent Contributions in Intelligent Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 657))

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Abstract

In this paper, a new technique based on interval-valued fuzzy sets and scale-space smoothing is proposed for image analysis and restoration. Interval-valued fuzzy sets (IVFS) are associated with type-2 semantic uncertainty that makes it possible to take into account usually ignored (or difficult to manage) stochastic errors during image acquisition. Indeed, the length of the interval (of IVFS) provides a new tool to define a particular resolution scale for scale-space smoothing. This resolution scale is constructed from two smoothed image histograms and is associated with interval-valued fuzzy entropy (IVF entropy). Then, IVF entropy is used for analyzing the image histogram to find the noisy pixels of images and to define an efficient image quality metric. To show the effectiveness of this new technique, we investigate two specific and significant image processing applications: no-reference quality evaluation of computer-generated images and speckle noise filtering.

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Author information

Authors and Affiliations

  1. LAGIS-UMR CNRS 8219, Université Lille 1, 59655, Villeneuve d’Ascq Cedex, France

    Olivier Colot

  2. LISIC-ULCO, 50 rue Ferdinand Buisson - BP 699, 62228, Calais Cedex, France

    Samuel Delepoulle, André Bigand & Christophe Renaud

Authors
  1. Samuel Delepoulle
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  2. André Bigand
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  3. Christophe Renaud
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  4. Olivier Colot
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Corresponding author

Correspondence to Samuel Delepoulle .

Editor information

Editors and Affiliations

  1. Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Vassil Sgurev

  2. Machine Intelligence Institute, Hagan School of Business, Iona College, New Rochelle, New York, USA

    Ronald R. Yager

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  4. Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria

    Krassimir T. Atanassov

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Delepoulle, S., Bigand, A., Renaud, C., Colot, O. (2017). Low-Level Image Processing Based on Interval-Valued Fuzzy Sets and Scale-Space Smoothing. In: Sgurev, V., Yager, R., Kacprzyk, J., Atanassov, K. (eds) Recent Contributions in Intelligent Systems. Studies in Computational Intelligence, vol 657. Springer, Cham. https://doi.org/10.1007/978-3-319-41438-6_1

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  • DOI: https://doi.org/10.1007/978-3-319-41438-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41437-9

  • Online ISBN: 978-3-319-41438-6

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