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Underwater Image Enhancement Based on Color Balance and Edge Sharpening

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Artificial Intelligence and Security (ICAIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12240))

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Abstract

Underwater optical images often suffer from color cast, edge-blurring and low contrast due to the medium absorption and scattering in water. To solve these problems, we propose an effective technique to improve underwater image quality. First, we introduce an effective color balance strategy based on affine transform to address the color distortion. Then we convert the underwater image from RGB color space to CIE-Lab color space for contrast improvement. In ‘L’ component’s nonsubsampled contourlet transform (NSCT) domain, global contrast adjustment and multi-scale edge sharpening are conducted respectively for lowpass and bandpass direction subbands. Finally, a color-corrected and contrast-enhanced output image can be generated by inverse NSCT and conversion back to RGB color space. The propose method is a single image approach that does not require prior knowledge about the underwater imaging conditions. Experimental results show that our method outperforms state-of-the-art methods both in qualitative and quantitative evaluation. It generally results in good perceptual quality, with significant enhancement of the global contrast, the color, and the image structure details.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 41706103) and the Natural Science Foundation of Jiangsu Province (No. BK20170306), and the Fundamental Research Funds for the Central Universities (No. 2017B17714).

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Authors and Affiliations

  1. College of Internet of Things Engineering, Hohai University, Changzhou, 213022, China

    Yan Zhou, Yibin Tang, Guanying Huo & Dabing Yu

  2. Changzhou Key Laboratory of Sensor Networks and Environmental Sensing, Changzhou, 213022, China

    Yan Zhou & Guanying Huo

Authors
  1. Yan Zhou
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  2. Yibin Tang
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  3. Guanying Huo
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  4. Dabing Yu
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Corresponding author

Correspondence to Yan Zhou .

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Editors and Affiliations

  1. Nanjing University of Information Science, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science, Nanjing, China

    Jinwei Wang

  3. Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Zhou, Y., Tang, Y., Huo, G., Yu, D. (2020). Underwater Image Enhancement Based on Color Balance and Edge Sharpening. In: Sun, X., Wang, J., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2020. Lecture Notes in Computer Science(), vol 12240. Springer, Cham. https://doi.org/10.1007/978-3-030-57881-7_64

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  • DOI: https://doi.org/10.1007/978-3-030-57881-7_64

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-57880-0

  • Online ISBN: 978-3-030-57881-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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