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Nature-Inspired Computing and Optimization pp 381–407Cite as

Brain Action Inspired Morphological Image Enhancement

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Part of the book series: Modeling and Optimization in Science and Technologies ((MOST,volume 10))

Abstract

The image perception by human brain through the eyes is not exactly what the eyes receive. In order to have an enhanced view of the received image and more clarity in detail, the brain naturally modifies the color tones in adjacent neighborhoods of colors. A very famous example of this human sight natural modification to the view is the famous Chevreul–Mach bands. In this phenomenon, every bar is filled with one solid level of gray, but human brain perceives narrow bands at the edges with increased contrast which does not reflect the physical reality of solid gray bars. This human visual system action in illusion, highlighting the edges, is inspired here in visual illusory image enhancement (VIIE). An algorithm for the newly introduced VIIE by deploying morphological filters is presented as morphological VIIE (MVIIE). It deploys morphological filters for boosting the same effect on the image edges and aiding human sight by increasing the contrast of the sight. MVIIE algorithm is explained in this chapter. Significant image enhancement, by MVIEE, is approved through the experiments in terms of image quality metrics and visual perception.

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Author information

Authors and Affiliations

  1. Faculty of Computers Networks and Security (CNS), University of Information Science and Technology, Ohrid, Republic of Macedonia

    Mahdi Khosravy

  2. Faculty of Machine Intelligence and Robotics (MIR), University of Information Science and Technology, Ohrid, Republic of Macedonia

    Neeraj Gupta

  3. University of Information Science and Technology, Ohrid, Republic of Macedonia

    Ninoslav Marina

  4. Department of Computer Science and Engineering, Oakland University, Rochester, Michigan, USA

    Ishwar K. Sethi

  5. Faculty of Engineering, Information Department, University of the Ryukyus, Okinawa, Japan

    Mohammad Reza Asharif

Authors
  1. Mahdi Khosravy
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  2. Neeraj Gupta
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  3. Ninoslav Marina
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  4. Ishwar K. Sethi
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  5. Mohammad Reza Asharif
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Corresponding author

Correspondence to Mahdi Khosravy .

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Editors and Affiliations

  1. Dept of Computer Science and Engineering, SOA University Dept of Computer Science and Engineering, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  2. School of Science and Technology, Middlesex University School of Science and Technology, London, United Kingdom

    Xin-She Yang

  3. School of H.S.E., University of Hyogo School of H.S.E., Himeji, Japan

    Kazumi Nakamatsu

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Khosravy, M., Gupta, N., Marina, N., Sethi, I.K., Asharif, M.R. (2017). Brain Action Inspired Morphological Image Enhancement. In: Patnaik, S., Yang, XS., Nakamatsu, K. (eds) Nature-Inspired Computing and Optimization. Modeling and Optimization in Science and Technologies, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-50920-4_15

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  • DOI: https://doi.org/10.1007/978-3-319-50920-4_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-50919-8

  • Online ISBN: 978-3-319-50920-4

  • eBook Packages: EngineeringEngineering (R0)

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