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Computational Intelligence in Data Mining - Volume 1 pp 243–250Cite as

Automatic Contrast Enhancement for Wireless Capsule Endoscopy Videos with Spectral Optimal Contrast-Tone Mapping

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Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 31))

Abstract

Wireless capsule endoscopy (WCE) is a revolutionary imaging method for visualizing gastrointestinal tract in patients. Each exam of a patient creates large-scale color video data typically in hours and automatic computer aided diagnosis (CAD) are of important in alleviating the strain on expert gastroenterologists. In this work we consider an automatic contrast enhancement method for WCE videos by using an extension of the recently proposed optimal contrast-tone mapping (OCTM) to color images. By utilizing the transformation of each RGB color from of the endoscopy video to the spectral color space La*b* and utilizing the OCTM on the intensity channel alone we obtain our spectral OCTM (SOCTM) approach. Experimental results comparing histogram equalization, anisotropic diffusion and original OCTM show that our enhancement works well without creating saturation artifacts in real WCE imagery.

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Acknowledgments

We would like to thank the Gastroenterologists Dr. R. Shankar, Dr. A. Sebastian from Vellore Christian Medical College Hospital, India for their help in interpreting WCE imagery.

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Authors and Affiliations

  1. Department of Computer Science, University of Missouri-Columbia, Columbia, 65211, USA

    V. B. Surya Prasath

  2. Cognitive Modeling Lab, IT University Innopolis, Kazan, Russia

    Radhakrishnan Delhibabu

  3. Artificial Consciousness Lab, Kazan Federal University, Kazan, Russia

    Radhakrishnan Delhibabu

  4. Department of Computer Science Engineering, SSN Engineering College, Chennai, 603110, India

    Radhakrishnan Delhibabu

Authors
  1. V. B. Surya Prasath
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  2. Radhakrishnan Delhibabu
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Corresponding author

Correspondence to V. B. Surya Prasath .

Editor information

Editors and Affiliations

  1. University of Canberra, Canberra, Australia and University of South Australia, Adelaide, South Australia, Australia

    Lakhmi C. Jain

  2. Department of Computer Science and Engineering, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  3. Computer Science & Engineering, Kalyani University, Nadia, West Bengal, India

    Jyotsna Kumar Mandal

  4. Dept. of Computer Science and Engineering, National Institute of Technology Rourkela, Rourkela, India

    Durga Prasad Mohapatra

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Surya Prasath, V.B., Delhibabu, R. (2015). Automatic Contrast Enhancement for Wireless Capsule Endoscopy Videos with Spectral Optimal Contrast-Tone Mapping. In: Jain, L., Behera, H., Mandal, J., Mohapatra, D. (eds) Computational Intelligence in Data Mining - Volume 1. Smart Innovation, Systems and Technologies, vol 31. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2205-7_23

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  • DOI: https://doi.org/10.1007/978-81-322-2205-7_23

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2204-0

  • Online ISBN: 978-81-322-2205-7

  • eBook Packages: EngineeringEngineering (R0)

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