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Multi-objective Swarm Intelligence pp 123–142Cite as

Ant Colony for Locality Foraging in Image Enhancement

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 592))

Abstract

This chapter presents a spatial color algorithm called Termite Retinex and the problem of filtering locality in this family of algorithms for image enhancement, inspired by the human vision system. The algorithm we present is a recent implementation of Retinex with a colony of agents, which uses swarm intelligence to explore the image, determining in this way the locality of its filtering. This results in an unsupervised detail enhancement, dynamic range stretching, color correction, and high dynamic range tone rendering. In the chapter we describe the characteristic of glocality (\(\mathrm{glocal} = \mathrm{global} + \mathrm{local}\)) of image exploration, and after a description of the Retinex spatial color algorithm family, we present the Termite approach and discuss results.

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Authors and Affiliations

  1. Department of Computer Science, Università degli Studi di Milano, Milano, Italy

    Gabriele Simone, Davide Gadia & Alessandro Rizzi

  2. The Norwegian Colour and Visual Computing Laboratory, Faculty of Computer Science and Media Technology, Gjøvik University College, Gjøvik, Norway

    Gabriele Simone & Ivar Farup

Authors
  1. Gabriele Simone
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  2. Davide Gadia
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  3. Ivar Farup
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  4. Alessandro Rizzi
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Corresponding author

Correspondence to Gabriele Simone .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Technology, Fakir Mohan University, Balasore, India

    Satchidananda Dehuri

  2. Department of Computer Science and Engineering, Siksha 'O' Anusandhan University, Bhubaneswar, India

    Alok Kumar Jagadev

  3. Gandhi Institute for Technological Advancement, Bhubaneswar, India

    Mrutyunjaya Panda

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Simone, G., Gadia, D., Farup, I., Rizzi, A. (2015). Ant Colony for Locality Foraging in Image Enhancement. In: Dehuri, S., Jagadev, A., Panda, M. (eds) Multi-objective Swarm Intelligence. Studies in Computational Intelligence, vol 592. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46309-3_5

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  • DOI: https://doi.org/10.1007/978-3-662-46309-3_5

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  • Print ISBN: 978-3-662-46308-6

  • Online ISBN: 978-3-662-46309-3

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