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On Evolutionary Integral Models for Image Restoration

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Developments in Medical Image Processing and Computational Vision

Part of the book series: Lecture Notes in Computational Vision and Biomechanics ((LNCVB,volume 19))

Abstract

This paper analyzes evolutionary integral based methods for image restoration. They are multiscale linear models where the restored image evolves according to a Volterra equation, and the diffusion is handled by a convolution kernel. Well-posedness, scale-space properties, and long term behaviour are investigated for the continuous and semi-discrete models. Some numerical experiments are included. They provide different rules to select the kernel, and illustrate the performance of the evolutionary integral model in image denoising and contour detection.

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Author information

Authors and Affiliations

  1. Department of Applied Mathematics, E.T.S.I. of Telecomunication, University of Valladolid, Valladolid, Spain

    E. Cuesta & A. Durán

  2. Laboratoire de Mathématiques, Image et Applications, Université de La Rochelle, Avenue M. Crépeau, 17042, La Rochelle Cedex, France

    M. Kirane

Authors
  1. E. Cuesta
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  2. A. Durán
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  3. M. Kirane
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Corresponding author

Correspondence to E. Cuesta .

Editor information

Editors and Affiliations

  1. Department of mechanical engineering, Universidade do Porto, Porto, Portugal

    João Manuel R. S. Tavares

  2. Universidade do Porto, Porto, Portugal

    Renato Natal Jorge

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Cuesta, E., Durán, A., Kirane, M. (2015). On Evolutionary Integral Models for Image Restoration. In: Tavares, J., Natal Jorge, R. (eds) Developments in Medical Image Processing and Computational Vision. Lecture Notes in Computational Vision and Biomechanics, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-13407-9_15

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  • DOI: https://doi.org/10.1007/978-3-319-13407-9_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13406-2

  • Online ISBN: 978-3-319-13407-9

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