Laser & Optoelectronics Progress, Volume. 60, Issue 4, 0401003(2023)

Underwater Image Restoration Based on Classification and Dark Channel Prior with Minimum Convolutional Area

Guodong Liu1, Lihui Feng1、*, Jihua Lu2、**, and Jianmin Cui1
Author Affiliations
  • 1School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China
  • 2School of Integrated Circuits and Electronics, Beijing Institute of Technology, Beijing 100081, China
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    Figures & Tables(11)
    Schematic diagram of underwater formation model
    Flowchart of HSV-CIELAB classification equalization and minimum convolution area DCP
    CIELAB color equalization results. (a) RGB channel grayscale of raw image; (b) RGB channel grayscale of balanced image
    Comparison of LAB histograms of images. (a) Channel L of raw image; (b) channel a of raw image; (c) channel b of raw image; (d) channel L of balanced image; (e) channel a of balanced image; (f) channel b of balanced image
    Composite false color image
    Backlight estimation. (a) Original image; (b) dark channel Dx; (c) convolution image G x
    Example of backlight estimation with minimum convolution area DCP algorithm
    Comparison of visual results of different algorithms. (a) (b) High-saturation distorted images; (c) (d) low-saturation distortion images; (e) (f) shallow water images
    Enhancement results of different algorithms and comparison with reference images. (a) (b) (c) High-saturation distorted images; (d) (e) (f) (g) (h) low-saturation distorted images; (i) shallow water image
    • Table 1. PSNR and SSIM evaluation quality of different algorithms

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      Table 1. PSNR and SSIM evaluation quality of different algorithms

      AlgorithmParameterUDCPULAPIBLAMIPProposed algorithm
      Image(a)PSNR10.891118.894718.787715.424419.1593
      SSIM0.48920.73770.76940.69690.7298
      Image(b)PSNR12.926917.503720.730419.320321.1145
      SSIM0.67790.70330.82950.75300.8716
      Image(c)PSNR12.538416.521317.451719.175421.9297
      SSIM0.63350.69130.63560.80480.8136
      Image(d)PSNR10.336417.096219.312316.628321.8104
      SSIM0.60460.79370.84630.77320.8943
      Image(e)PSNR15.793618.863017.614817.747822.7959
      SSIM0.51970.80530.87040.85020.8880
      Image(f)PSNR15.821917.345616.453916.759118.3918
      SSIM0.73150.85100.80770.79590.8590
      Image(g)PSNR11.110515.979516.361416.142420.3412
      SSIM0.69590.83650.83510.82620.8878
      Image(h)PSNR18.040521.397320.764221.145522.7646
      SSIM0.83910.91160.92830.93380.9188
      Image(i)PSNR13.544213.619615.822713.573718.6227
      SSIM0.73190.76330.61390.75660.8931
    • Table 2. Parameters of UCIQE of different algorithms

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      Table 2. Parameters of UCIQE of different algorithms

      AlgorithmUDCPULAPIBLAMIPProposed algorithmReference
      Image(a)0.46290.53400.56220.52750.57100.5777
      Image(b)0.57510.58270.60990.61050.59340.5778
      Image(c)0.48690.55270.47440.54510.57560.5718
      Image(d)0.45920.57120.55020.51090.57460.5581
      Image(e)0.53190.57380.59120.58870.58290.6139
      Image(f)0.53860.58490.59060.55450.58370.5031
      Image(g)0.55700.58170.58640.58980.60810.6074
      Image(h)0.58180.60220.56800.58620.56850.5670
      Image(i)0.52440.54650.53150.54980.55410.5287
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    Guodong Liu, Lihui Feng, Jihua Lu, Jianmin Cui. Underwater Image Restoration Based on Classification and Dark Channel Prior with Minimum Convolutional Area[J]. Laser & Optoelectronics Progress, 2023, 60(4): 0401003

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    Paper Information

    Category: Atmospheric Optics and Oceanic Optics

    Received: Jan. 27, 2022

    Accepted: Mar. 30, 2022

    Published Online: Feb. 14, 2023

    The Author Email: Feng Lihui (lihui.feng@bit.edu.cn), Lu Jihua (lujihua@bit.edu.cn)

    DOI:10.3788/LOP220651

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