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A Robust and Fast Fundus Image Enhancement by Dehazing

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • C. Aruna Vinodhini

    (Anna University
    Anna University Regional Center, Department of Computer Science and Engineering)

  • S. Sabena

    (Anna University
    Anna University Regional Center, Department of Computer Science and Engineering)

  • L. Sai Ramesh

    (Anna University
    Anna University Regional Center, Department of Computer Science and Engineering)

Abstract

Retinal fundus images are important for the identification and detection of vision- related diseases such as diabetes and hypertension. From an acquisition process, retinal images often have large luminosity, noise and low contrast which seriously affect the automated system of deriving diagnostic parameters. In this paper, a new faster method of correcting luminosity by de-hazing is applied. This method corrects the non-uniform illumination in the intensity domain and then the contrast enhancement is performed along with filtering. Experiments were performed on the publicly available retinal image dataset DRIVE AND DIARETDB1.

Suggested Citation

  • C. Aruna Vinodhini & S. Sabena & L. Sai Ramesh, 2020. "A Robust and Fast Fundus Image Enhancement by Dehazing," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1111-1119, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_113
    DOI: 10.1007/978-3-030-41862-5_113
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