• Laser & Optoelectronics Progress
  • Vol. 61, Issue 8, 0837001 (2024)
Ning Yang1、2、3, Haibing Su1、2、3、4、*, and Tao Zhang1、2、4
Author Affiliations
  • 1Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, Sichuan , China
  • 2National Key Laboratory of Optical Field Manipulation Science and Technology, Chinese Academy of Sciences, Chengdu 610209, Sichuan , China
  • 3School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
  • 4School of Optoelectronics, University of Chinese Academy of Sciences, Beijing 100049, China
  • show less
    DOI: 10.3788/LOP231335 Cite this Article Set citation alerts
    Ning Yang, Haibing Su, Tao Zhang. Adaptive Underwater Image Enhancement Algorithm[J]. Laser & Optoelectronics Progress, 2024, 61(8): 0837001 Copy Citation Text show less
    Algorithm flow chart
    Fig. 1. Algorithm flow chart
    Results of adaptive color equalization. (a) Original images; (b) processing results of gray world algorithm; (c) processing results of adaptive color balance
    Fig. 2. Results of adaptive color equalization. (a) Original images; (b) processing results of gray world algorithm; (c) processing results of adaptive color balance
    Results of adaptive global contrast enhancement. (a) Original images; (b) processing results of adaptive color equalization; (c) processing results of adaptive global contrast enhancement
    Fig. 3. Results of adaptive global contrast enhancement. (a) Original images; (b) processing results of adaptive color equalization; (c) processing results of adaptive global contrast enhancement
    Processing results of underwater images in low light. (a) Original images; (b) processing results of adaptive color equalization; (c) processing results of adaptive global contrast enhancement
    Fig. 4. Processing results of underwater images in low light. (a) Original images; (b) processing results of adaptive color equalization; (c) processing results of adaptive global contrast enhancement
    Results of adaptive underwater image enhancement algorithm. (a) Original images; (b)‒(d) processing results of adaptive color equalization, adaptive global contrast enhancement, and adaptive detail enhancement
    Fig. 5. Results of adaptive underwater image enhancement algorithm. (a) Original images; (b)‒(d) processing results of adaptive color equalization, adaptive global contrast enhancement, and adaptive detail enhancement
    Subjective comparison of results using different methods. (a) Original images; (b)‒(g) processing results of UDCP, fusion method, UTV, ULV, L2UWE, and the proposed method
    Fig. 6. Subjective comparison of results using different methods. (a) Original images; (b)‒(g) processing results of UDCP, fusion method, UTV, ULV, L2UWE, and the proposed method
    MetricMethodimage 1image 2image 3image 4image 5
    UCIQEUDCP60.25870.25870.25870.25870.5321
    Fusion method140.48420.51320.49220.56550.4753
    UTV80.40240.44710.55840.60780.3593
    L2UWE130.25870.25870.25880.25940.2587
    ULV250.47590.53450.57190.62850.4817
    Proposed method0.58820.62340.60720.59410.5673
    CCFUDCP614.058716.770016.708514.84074.5165
    Fusion method1414.458916.998517.512920.975822.3465
    UTV847.482611.594521.977245.225512.4622
    L2UWE1316.260716.356715.242818.063510.1131
    ULV2511.062616.519720.241131.482821.4070
    Proposed method26.196237.261527.828445.416033.0953
    Information entropyUDCP67.19437.32655.70075.62446.0584
    Fusion method147.46717.14287.32107.11937.0869
    UTV86.65846.50445.54325.10105.8684
    L2UWE137.76597.43587.57947.24017.5575
    ULV257.66637.39897.83706.48506.2104
    Proposed method7.81387.78937.83557.35097.6475
    Table 1. Objective quality evaluation of Fig. 6
    MethodUDCP6Fusion method14UTV8L2UWE13ULV25Proposed method
    UCIQE0.59730.55540.56600.55900.60570.6125
    CCF27.493822.079627.493832.669027.945734.6980
    Information entropy6.78327.41146.11157.50797.45377.6425
    Table 2. Average quantitative evaluation of different methods.
    MethodUDCP6Fusion method14UTV8L2UWE13ULV25Proposed method
    Time37.5571.84053.581845.78998.05170.3692
    Table 3. Average running time of different methods
    Ning Yang, Haibing Su, Tao Zhang. Adaptive Underwater Image Enhancement Algorithm[J]. Laser & Optoelectronics Progress, 2024, 61(8): 0837001
    Download Citation