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Laser & Optoelectronics Progress, Volume. 58, Issue 14, 1410004(2021)

Underwater Image Enhancement Based on Differential Channel Gain and Improved Retinex

Caizhen Zhang, Binlong Kang*, Ying Li, and Yuan Chang
Author Affiliations
  • School of Electronic and Information Engineering, LanZhou JiaoTong Univercity, Lanzhou, Gansu 730070, China
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    AbstractGet PDF(in Chinese)
    Figures&Tables (8)
    Equations (0)
    References (19)
    Cited By (5)
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    Figures & Tables(8)
    Underwater optical imaging model

    Fig. 1. Underwater optical imaging model

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    Graphic comparison of two functions. (a) log function; (b) tanh function

    Fig. 2. Graphic comparison of two functions. (a) log function; (b) tanh function

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    Effects of different algorithms before and after processing. (a) Original images; (b) traditional MSR algorithm; (c) improved MSR algorithm

    Fig. 3. Effects of different algorithms before and after processing. (a) Original images; (b) traditional MSR algorithm; (c) improved MSR algorithm

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    Processing results of character image. (a) Original images; (b) Ref. [8]; (c) Ref. [9]; (d) Ref. [13]. (e) proposed algorithm

    Fig. 4. Processing results of character image. (a) Original images; (b) Ref. [8]; (c) Ref. [9]; (d) Ref. [13]. (e) proposed algorithm

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    Processing results of fish swarm images. (a) Original images; (b) Ref. [8]; (c) Ref. [9]; (d) Ref. [13]. (e) proposed algorithm

    Fig. 5. Processing results of fish swarm images. (a) Original images; (b) Ref. [8]; (c) Ref. [9]; (d) Ref. [13]. (e) proposed algorithm

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    Processing results of coral images. (a) Original images; (b) Ref. [8]; (c) Ref. [9]; (d) Ref. [13]. (e) proposed algorithm

    Fig. 6. Processing results of coral images. (a) Original images; (b) Ref. [8]; (c) Ref. [9]; (d) Ref. [13]. (e) proposed algorithm

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    • Table 1. Information entropy values of each algorithms

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      Table 1. Information entropy values of each algorithms

      ImageOiginalRef. [8]Ref. [9]Ref. [13]Proposed algorithm
      Oiginal image7.58447.60427.49867.72057.9162
      Fig. 4 image 17.35216.78817.12907.45987.8942
      Fig. 4 image 26.67636.68326.22387.66317.8457
      Fig. 5 image 17.71707.73347.60597.86757.8888
      Fig. 5 image 27.30347.37967.18827.86657.8436
      Fig. 6 image 17.42347.51057.54297.92497.9353

    • Table 2. Standard deviation values of each algorithms

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      Table 2. Standard deviation values of each algorithms

      ImageOriginalRef. [8]Ref. [9]Ref. [13]Proposed algorithm
      Fig. 4 image 16.97297.60507.86888.31208.3455
      Fig. 4 image 25.85277.30177.18248.02038.0565
      Fig. 5 image 15.40777.40117.81737.94978.0185
      Fig. 5 image 27.55247.76087.66688.17438.2145
      Fig. 6 image 16.77717.59268.00927.86677.9521
      Fig. 6 image 17.15347.54858.10608.05328.1202
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    Caizhen Zhang, Binlong Kang, Ying Li, Yuan Chang. Underwater Image Enhancement Based on Differential Channel Gain and Improved Retinex[J]. Laser & Optoelectronics Progress, 2021, 58(14): 1410004

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    Paper Information

    Category: Image Processing

    Received: Oct. 10, 2020

    Accepted: Nov. 12, 2020

    Published Online: Jul. 8, 2021

    The Author Email: Binlong Kang (570384183@qq.com)

    DOI:10.3788/LOP202158.1410004

    Topics

    laser devices and laser physics
    Lasers and Laser Optics
    Laser physics
    laser manufacturing
    Instrumentation, Measurement and Metrology