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Enhancement of underwater images by super-resolution generative adversarial networks

Published: 17 August 2018 Publication History

Abstract

Underwater image enhancement plays an important role in oceanic engineering, while the research is far from enough. The problems like color casts, low contrast brought out by the properties of water and its impurities, make it a challenging task. This paper proposes a novel framework for enhancing underwater image. It includes two parts, that is, pre-processing and de-blurring with improved Super-resolution Generative Adversarial Networks. First, in the process of pre-processing, we use the color correction approach and the contrast enhancement method to compensate color casts and produce natural color images. Second, an improved Super-resolution Generative Adversarial Networks is applied to pre-processed images in order to remove blurring and boost detail. Based on the network, the loss net is modified, so that the pre-processed images will be de-blurred and sharpened. The experimental results show that the proposed strategy improves the quality of underwater images efficiently.

References

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and L. Theis C. Ledig and J. Caballero. 2017. Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2017), 1063--6919.
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Hitam and Muhammad Suzuri. 2013. Mixture contrast limited adaptive histogram equalization for underwater image enhancement. Proc. International Conference on Computer Applications Technology (ICCAT) (2013), 1--5.
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and Ali Farhadi. Joseph Redmon. 2017. YOLOv3: An Incremental Improvement. (2017). https://pjreddie.com/darknet/ code:.
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He K., Sun J., and Tang X. 2011. Single image haze removal using dark channel prior. IEEE transactions on pattern analysis and machine intelligence 33, 12 (2011), 2341--2353.
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Li X., Yang Z., and Shang M. 2016. Underwater image enhancement via dark channel prior and luminance adjustment. Oceans. IEEE (2016), 1--5.
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and R. Wang and J. Zhang Y. Wang, and X. Ding and X. Fu. 2017. Fusion-based underwater image enhancement by wavelet decomposition. IEEE International Conference on Industrial Technology (ICIT) (2017), 1013--1018.

Cited By

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  • (2023)Simultaneous restoration and super-resolution GAN for underwater image enhancementFrontiers in Marine Science10.3389/fmars.2023.116229510Online publication date: 21-Jun-2023
  • (2023)Underwater Image Enhancement Based on 2D Cubic Spline Wavelet and Red Channel PriorJournal of Image and Signal Processing10.12677/JISP.2023.12100612:01(51-60)Online publication date: 2023
  • (2022)Underwater Image Enhancement Using Laplace DecompositionIEEE Geoscience and Remote Sensing Letters10.1109/LGRS.2020.302113419(1-5)Online publication date: 2022
  • Show More Cited By

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  1. Enhancement of underwater images by super-resolution generative adversarial networks

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    cover image ACM Other conferences
    ICIMCS '18: Proceedings of the 10th International Conference on Internet Multimedia Computing and Service
    August 2018
    243 pages
    ISBN:9781450365208
    DOI:10.1145/3240876
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 17 August 2018

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    Author Tags

    1. color correction
    2. contrast enhancement
    3. super-resolution generative adversarial networks
    4. underwater image

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    ICIMCS '18 Paper Acceptance Rate 46 of 116 submissions, 40%;
    Overall Acceptance Rate 163 of 456 submissions, 36%

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    Cited By

    View all
    • (2023)Simultaneous restoration and super-resolution GAN for underwater image enhancementFrontiers in Marine Science10.3389/fmars.2023.116229510Online publication date: 21-Jun-2023
    • (2023)Underwater Image Enhancement Based on 2D Cubic Spline Wavelet and Red Channel PriorJournal of Image and Signal Processing10.12677/JISP.2023.12100612:01(51-60)Online publication date: 2023
    • (2022)Underwater Image Enhancement Using Laplace DecompositionIEEE Geoscience and Remote Sensing Letters10.1109/LGRS.2020.302113419(1-5)Online publication date: 2022
    • (2022)Underwater image enhancement by combining color constancy and dehazing based on depth estimationNeurocomputing10.1016/j.neucom.2021.07.003460:C(211-230)Online publication date: 22-Apr-2022

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