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Enhancement of Low-Lighting Underwater Images Using Dark Channel Prior and Fast Guided Filters

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Pattern Recognition and Information Forensics (ICPR 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11188))

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Abstract

Low levels of lighting in images and videos may lead to poor results in segmentation, detection, tracking, among numerous other computer vision tasks. Deep-sea camera systems, such as those deployed on the Ocean Networks Canada (ONC) cabled ocean observatories, use artificial lighting to illuminate and capture videos of deep-water biological environments. When these lighting systems fail, the resulting images become hard to interpret or even completely useless because of their lighting levels. This paper proposes an effective framework to enhance the lighting levels of underwater images, increasing the number of visible, meaningful features. The process involves the dehazing of images using a dark channel prior and fast guided filters.

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Author information

Authors and Affiliations

  1. University of Victoria, Victoria, BC, V8P5C2, Canada

    Tunai Porto Marques & Alexandra Branzan Albu

  2. Ocean Networks Canada, Victoria, BC, V8P5C2, Canada

    Maia Hoeberechts

Authors
  1. Tunai Porto Marques
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  2. Alexandra Branzan Albu
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  3. Maia Hoeberechts
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Corresponding authors

Correspondence to Tunai Porto Marques , Alexandra Branzan Albu or Maia Hoeberechts .

Editor information

Editors and Affiliations

  1. Chinese Academy of Sciences, Beijing, China

    Zhaoxiang Zhang

  2. University of Adelaide, North Terrace, SA, Australia

    David Suter

  3. City College of New York, New York, NY, USA

    Yingli Tian

  4. University of Victoria, Victoria, BC, Canada

    Alexandra Branzan Albu

  5. University of La Rochelle, La Rochelle, France

    Nicolas Sidère

  6. National Institute of Astrophysics, Optics and Electronics, Puebla, Mexico

    Hugo Jair Escalante

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Marques, T.P., Albu, A.B., Hoeberechts, M. (2019). Enhancement of Low-Lighting Underwater Images Using Dark Channel Prior and Fast Guided Filters. In: Zhang, Z., Suter, D., Tian, Y., Branzan Albu, A., Sidère, N., Jair Escalante, H. (eds) Pattern Recognition and Information Forensics. ICPR 2018. Lecture Notes in Computer Science(), vol 11188. Springer, Cham. https://doi.org/10.1007/978-3-030-05792-3_6

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  • DOI: https://doi.org/10.1007/978-3-030-05792-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05791-6

  • Online ISBN: 978-3-030-05792-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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