Laser & Optoelectronics Progress, Volume. 59, Issue 19, 1933001(2022)

Spectral Reconstruction Algorithm Based on Multi-Light Source Wiener Estimation

Han Wang and Changjun Li*
Author Affiliations
  • School of Computer and Software Engineering, University of Science and Technology Liaoning, Anshan 114051, Liaoning, China
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    Figures & Tables(11)
    Experimental sample (a) ColorChecker White Balance; (b) ColorChecker Digital 140; (c) Munsell sample
    Light sources provided by SpectraLight QC
    Spectral sensitivity function of the digital camera. (a) Canon EOS 60D; (b) Nikon D610
    DWE algorithm reconstructs the sample corresponding to the maximum RMSE and maximum chromatic aberration. (a) Maximum RMSE; (b) maximum color difference
    Spectral reflectance corresponding to the minimum RPD of different algorithms. (a) WE; (b) Nonlin; (c) Wt-nonlin; (d) ALWL; (e) ZHANG; (f) DWE
    • Table 1. Combinations of light sources

      View table

      Table 1. Combinations of light sources

      No.D65U30HZTL84CWFA
      1×××××
      2××××
      3×××
      4××
      5×
      6
    • Table 2. Reflectance reconstruction results for Canon camera

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      Table 2. Reflectance reconstruction results for Canon camera

      No.Chromatic aberrationRMSE
      MeanMedianMaxMeanMedianMax
      13.09602.489814.86740.03740.03340.1252
      21.86431.66326.69340.03400.02930.1263
      31.58661.39886.11910.02900.02340.0892
      41.83811.605013.80840.02890.02260.0875
      51.84001.586813.65950.02670.02200.0822
      62.78662.480415.57740.03090.02620.0852
    • Table 3. Reflectance reconstruction results for Nikon camera

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      Table 3. Reflectance reconstruction results for Nikon camera

      No.Chromatic aberrationRMSE
      MeanMedianMaxMeanMedianMax
      13.36013.074913.19250.03620.03190.1387
      21.82471.47379.34100.03280.02820.1274
      31.40111.24744.80990.02410.02100.1106
      41.85621.65056.42030.03140.02910.1111
      51.67591.50615.55610.02820.02550.1064
      61.57561.35735.36280.02770.02490.1099
    • Table 4. Spectral reflectance reconstruction results of different algorithms based on Canon cameras

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      Table 4. Spectral reflectance reconstruction results of different algorithms based on Canon cameras

      AlgorithmChromatic aberrationRMSE
      MeanMedianMaxMeanMedianMax
      WE3.10(6)2.49(6)14.87(6)0.037(6)0.033(6)0.125(6)
      Nonlin1.99(5)1.78(5)6.19(3)0.038(5)0.035(5)0.110(5)
      Wt-nonlin1.84(3)1.71(2)7.21(4)0.031(3)0.031(3)0.082(1)
      ALWL1.88(4)1.73(4)12.70(5)0.029(1)0.026(2)0.084(2)
      ZHANG1.79(2)1.72(3)5.78(1)0.034(4)0.032(4)0.085(3)
      DWE1.59(1)1.40(1)6.12(2)0.029(1)0.023(1)0.089(4)
    • Table 5. Spectral reflectance reconstruction results of different methods based on Nikon cameras

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      Table 5. Spectral reflectance reconstruction results of different methods based on Nikon cameras

      AlgorithmChromatic aberrationRMSE
      MeanMedianMaxMeanMedianMax
      WE3.36(6)3.07(6)13.19(5)0.036(5)0.032(6)0.139(6)
      Nonlin2.09(5)1.73(5)8.12(3)0.036(5)0.031(5)0.113(5)
      Wt-nonlin1.85(4)1.59(3)8.82(4)0.029(3)0.028(3)0.091(3)
      ALWL1.73(2)1.47(2)13.33(6)0.026(2)0.023(2)0.073(1)
      ZHANG1.77(3)1.61(4)5.94(2)0.032(4)0.029(4)0.085(2)
      DWE1.40(1)1.25(1)4.81(1)0.024(1)0.021(1)0.111(4)
    • Table 6. RPD of different algorithms

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      Table 6. RPD of different algorithms

      AlgorithmCanonNikon
      MeanMedianMinMeanMedianMin
      WE2.39572.12950.03922.56042.20190.0426
      Nonlin2.64442.1380.00972.83822.28990.0097
      Wt-nonlin3.32762.18320.02633.61242.43140.0268
      ALWL3.56932.53220.03213.8642.80860.0325
      ZHANG2.87412.13680.01663.06792.37530.0147
      DWE3.59682.75970.0414.02492.99890.0410
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    Han Wang, Changjun Li. Spectral Reconstruction Algorithm Based on Multi-Light Source Wiener Estimation[J]. Laser & Optoelectronics Progress, 2022, 59(19): 1933001

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    Paper Information

    Category: Vision, Color, and Visual Optics

    Received: Aug. 23, 2021

    Accepted: Sep. 27, 2021

    Published Online: Sep. 23, 2022

    The Author Email: Li Changjun (cjliustl@sina.com)

    DOI:10.3788/LOP202259.1933001

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