• Acta Optica Sinica
  • Vol. 39, Issue 11, 1111003 (2019)
Jiejun Wang1、2, Lei Liang1、2, Shu Li1、2、*, Song Ye1、2, and Fangyuan Wang1、2
Author Affiliations
  • 1School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China
  • 2Guangxi Key Laboratory of Photoelectric Information Processing, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China
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    DOI: 10.3788/AOS201939.1111003 Cite this Article Set citation alerts
    Jiejun Wang, Lei Liang, Shu Li, Song Ye, Fangyuan Wang. Correction and Implementation of Polarization-Difference Imaging Model for Underwater Target[J]. Acta Optica Sinica, 2019, 39(11): 1111003 Copy Citation Text show less
    Schematic of underwater imaging experimental apparatus
    Fig. 1. Schematic of underwater imaging experimental apparatus
    Ceramic images with different linear polarization directions. (a) 0°; (b) 45°; (c) 90°
    Fig. 2. Ceramic images with different linear polarization directions. (a) 0°; (b) 45°; (c) 90°
    Pre-processed intensity image
    Fig. 3. Pre-processed intensity image
    Restored image obtained by conventional underwater polarization difference imaging model
    Fig. 4. Restored image obtained by conventional underwater polarization difference imaging model
    Restored scene image obtained by improved model
    Fig. 5. Restored scene image obtained by improved model
    Estimation of correction parameter ε of ceramic restoration images. (a) Relationship among correction parameter ε, contrast, and information entropy; (b) relationship among correction parameter ε, average gradient, and information entropy
    Fig. 6. Estimation of correction parameter ε of ceramic restoration images. (a) Relationship among correction parameter ε, contrast, and information entropy; (b) relationship among correction parameter ε, average gradient, and information entropy
    Comparison of glass fiber board imaging. (a) Pre-processed intensity image; (b) image restored by conventional underwater polarization difference imaging model; (c) image restored by improved model
    Fig. 7. Comparison of glass fiber board imaging. (a) Pre-processed intensity image; (b) image restored by conventional underwater polarization difference imaging model; (c) image restored by improved model
    Comparison of rusty blade imaging. (a) Pre-processed intensity image; (b) image restored by conventional underwater polarization difference imaging model; (c) image restored by improved model
    Fig. 8. Comparison of rusty blade imaging. (a) Pre-processed intensity image; (b) image restored by conventional underwater polarization difference imaging model; (c) image restored by improved model
    Estimation of correction parameter ε of glass fiber board restoration images. (a) Relationship among correction parameter ε, contrast, and information entropy; (b) relationship among correction parameter ε, average gradient, and information entropy
    Fig. 9. Estimation of correction parameter ε of glass fiber board restoration images. (a) Relationship among correction parameter ε, contrast, and information entropy; (b) relationship among correction parameter ε, average gradient, and information entropy
    Estimation of correction parameter ε of rusty blade restoration images. (a) Relationship among correction parameter ε, contrast, and information entropy; (b) relationship among correction parameter ε, average gradient, and information entropy
    Fig. 10. Estimation of correction parameter ε of rusty blade restoration images. (a) Relationship among correction parameter ε, contrast, and information entropy; (b) relationship among correction parameter ε, average gradient, and information entropy
    ImageContrastContrast increment /%Information entropyInformation entropy increment /%Average gradient
    Fig. 30.15246.73540.0047
    Fig. 40.37571467.443110.50.0178
    Fig. 50.60742987.526011.70.0338
    Table 1. Comparison of experimental results
    ImageContrastContrast increment /%Information entropyInformation entropy increment /%Average gradient
    Fig. 7(a)0.10486.08260.0043
    Fig. 7(b)0.32452097.247619.10.0168
    Fig. 7(c)0.45733367.4838230.0269
    Fig. 8(a)0.15576.65130.0046
    Fig. 8(b)0.34861237.30999.90.0146
    Fig. 8(c)0.50652257.593114.20.0239
    Table 2. Comparison of experimental results
    Jiejun Wang, Lei Liang, Shu Li, Song Ye, Fangyuan Wang. Correction and Implementation of Polarization-Difference Imaging Model for Underwater Target[J]. Acta Optica Sinica, 2019, 39(11): 1111003
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