• Spectroscopy and Spectral Analysis
  • Vol. 41, Issue 7, 2219 (2021)
Xiao-yan WANG1、*, Jie LI2、2; *;, Bang-ping PENG1、1;, and Yi-cheng TU3、3;
Author Affiliations
  • 11. School of Information, Beijing Wuzi University, Beijing 101149, China
  • 22. School of Mechanical-electronic and Vehicle Engineering, University of Civil Engineering and Architecture, Beijing 102616, China
  • 33. Department of Computer Science and Engineering, University of South Florida, Fl, 33647, USA
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    DOI: 10.3964/j.issn.1000-0593(2021)07-2219-07 Cite this Article
    Xiao-yan WANG, Jie LI, Bang-ping PENG, Yi-cheng TU. Restoration of High-Frequency Vibration Blurred Hyperspectral Image Based on Dynamic Chaos Disturbance Genetic Algorithm[J]. Spectroscopy and Spectral Analysis, 2021, 41(7): 2219 Copy Citation Text show less
    Flowchart of dynamic chaos disturbance genetic algorithm
    Fig. 1. Flowchart of dynamic chaos disturbance genetic algorithm
    Hymap spectral data cube
    Fig. 2. Hymap spectral data cube
    Original image
    Fig. 3. Original image
    Flowchart of spectral image cube restoration
    Fig. 4. Flowchart of spectral image cube restoration
    Vibration degradation image
    Fig. 5. Vibration degradation image
    Richardson-Lucy restoration
    Fig. 6. Richardson-Lucy restoration
    Genetic algorithm restoration
    Fig. 7. Genetic algorithm restoration
    Dynamic chaos disturbance genetic algorithm restoration
    Fig. 8. Dynamic chaos disturbance genetic algorithm restoration
    Spectra of point (110, 22)
    Fig. 9. Spectra of point (110, 22)
    Spectra of point (210, 142)
    Fig. 10. Spectra of point (210, 142)
    Vibration degradation image
    Fig. 11. Vibration degradation image
    Richardson-Lucy restoration
    Fig. 12. Richardson-Lucy restoration
    Genetic algorithm restoration
    Fig. 13. Genetic algorithm restoration
    Dynamic chaos disturbance genetic algorithm restoration
    Fig. 14. Dynamic chaos disturbance genetic algorithm restoration
    Spectra of point (208, 123)
    Fig. 15. Spectra of point (208, 123)
    Spectra of point (191, 96)
    Fig. 16. Spectra of point (191, 96)
    图像有参评价无参评价
    SNRPSNRGMGLS
    原图--26.846 1133.078 6
    退化图3.254 316.897 213.484 268.092 3
    GA复原11.115 123.735 323.087 6116.099 7
    RL复原8.256 622.524 929.645 6138.920 7
    CGA复原13.231 724.234 130.723 4165.724 1
    Table 1. Objective assessment of image quality
    光谱数据立方体光谱信息散
    度(SID)
    光谱梯度
    角(SGA)
    原光谱立方体--
    畸变光谱立方体1.037 20.987 2
    GA复原光谱立方体1.028 80.973 6
    RL复原光谱立方体0.799 80.897 2
    CGA复原光谱立方体0.628 50.853 0
    Table 2. Spectral quality evaluation of spectral cube
    图像有参评价无参评价
    SNRPSNRGMGLS
    原图--26.846 1133.078 6
    退化图10.110 423.871 816.845 267.759 5
    GA复原11.470 123.998 925.982 0128.12
    RL复原12.582 424.351 526.775 1137.024 4
    CGA复原17.291 726.935 229.727 3152.301 2
    Table 3. Objective assessment of image quality
    光谱数据立方体光谱信息散
    度(SID)
    光谱梯度
    角(SGA)
    原光谱立方体--
    b畸变光谱立方体0.901 70.807 3
    GA复原光谱立方体0.899 10.791 5
    RL复原光谱立方体0.857 60.662 3
    CGA复原光谱立方体0.544 90.662 1
    Table 4. Spectral quality evaluation of spectral cube
    Xiao-yan WANG, Jie LI, Bang-ping PENG, Yi-cheng TU. Restoration of High-Frequency Vibration Blurred Hyperspectral Image Based on Dynamic Chaos Disturbance Genetic Algorithm[J]. Spectroscopy and Spectral Analysis, 2021, 41(7): 2219
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