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Effectual Single Image Dehazing with Color Correction Transform and Dark Channel Prior

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Data Science and Computational Intelligence (ICInPro 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1483))

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Abstract

Image acquisition during bad weather conditions like haze may adversely affect the quality and information processing. The image degradation affects object detection, which plays a prominent role in computer vision applications. Restoration of hazy images is necessary for exact identification and location of objects. This paper proposes a new prior based dehazing algorithm named Color Correction Transform Dark Channel Prior (CCTDCP). The proposed algorithm utilizes white balance color correction transform, dark channel prior and gamma correction for retaining the originality of the image. The experimental results on benchmark images exhibit superior performance of CCTDCP algorithm over the state-of-the-art methods.

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Acknowledgement

This work is supported by IIT Palakkad Technology IHub Foundation Doctoral Fellowship IPTIF/HRD/DF/021.

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Authors and Affiliations

  1. Indian Institute of Information Technology, Kottayam, Kerala, India

    Jeena Thomas & Ebin Deni Raj

Authors
  1. Jeena Thomas
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  2. Ebin Deni Raj
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Corresponding author

Correspondence to Ebin Deni Raj .

Editor information

Editors and Affiliations

  1. Bangalore University, Bengaluru, India

    K. R. Venugopal

  2. Bangalore University, Bengaluru, India

    P. Deepa Shenoy

  3. University of Melbourne, Melbourne, VIC, Australia

    Rajkumar Buyya

  4. NIAS, Bengaluru, India

    L. M. Patnaik

  5. Florida International University, Miami, FL, USA

    Sitharama S. Iyengar

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Thomas, J., Raj, E.D. (2021). Effectual Single Image Dehazing with Color Correction Transform and Dark Channel Prior. In: Venugopal, K.R., Shenoy, P.D., Buyya, R., Patnaik, L.M., Iyengar, S.S. (eds) Data Science and Computational Intelligence. ICInPro 2021. Communications in Computer and Information Science, vol 1483. Springer, Cham. https://doi.org/10.1007/978-3-030-91244-4_3

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  • DOI: https://doi.org/10.1007/978-3-030-91244-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91243-7

  • Online ISBN: 978-3-030-91244-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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