Laser & Optoelectronics Progress, Volume. 58, Issue 22, 2230003(2021)

Multi-Spectral Color Data Dimension Reduction Model Research Based on Sparse Representation

Xinyi Fang1... Xiaoxia Wan1,*, Shuo Shi2, Xiao Teng1 and Junyan Yu1 |Show fewer author(s)
Author Affiliations
  • 1Color Science Laboratory, School of Printing and Packaging, Wuhan University, Wuhan, Hubei 430079, China
  • 2State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan, Hubei 430079, China
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    Figures & Tables(6)
    RMSE distribution of each sample with SG color card as training set and Munsell color block as testset when each sample is reduced to six dimensions and reconstructed. (a) Spectral error distribution diagram obtained by PCA method; (b) spectral error distribution diagram obtained by SR method; (c) RMSE curve obtained by PCA method; (d) RMSE curve obtained by SR method
    Partial sample spectral reflectance curve, and reconstructed spectral curve based on PCA method and SR method. (a) Samples with high fitting degree; (b) samples of general fitness; (c) samples with poor fit
    Multispectral images from the University of Eastern Finland spectral image database. (a) Original image; (b) image reduced in dimension and reconstructed by SR method
    • Table 1. Comparison of spectral reconstruction accuracy between SR method and PCA method

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      Table 1. Comparison of spectral reconstruction accuracy between SR method and PCA method

      DatasetDimensionMethodRMSEGFC /%
      MeanMaxMinMeanMaxMin
      Munsell-SG6PCA0.0170.0480.00399.82599.99998.066
      SR0.0110.0390.00299.88499.99897.905
      5
      PCA0.0160.0440.00499.79799.99797.626
      SR0.0150.0400.00299.82899.99497.620
      4
      PCA0.0200.0680.00499.62699.99593.961
      SR0.0190.0680.00399.64899.99493.779
      3
      PCA0.0260.0850.00699.31499.99293.793
      SR0.0250.0860.00399.37599.98493.485
      SG-Munsell6PCA0.0680.6550.00599.29899.99376.455
      SR0.0100.0640.00199.90099.99792.273
      5
      PCA0.0510.3230.00599.45099.99369.969
      SR0.0150.0660.00299.80599.99791.971
      4
      PCA0.0470.2530.00599.38399.99377.736
      SR0.0180.0880.00299.66799.99786.454
      3
      PCA0.0410.1020.00499.33599.98685.781
      SR0.0250.0980.00299.41599.99484.614
    • Table 2. Comparison of chromaticity reconstruction accuracy between SR method and PCA method, under D65 light source

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      Table 2. Comparison of chromaticity reconstruction accuracy between SR method and PCA method, under D65 light source

      DatasetMethodΔE00
      MeanMaxMin
      Munsell-SGPCA1.5179.9040.047
      SR0.4512.3280.049
      SG-MunsellPCA5.93952.7270.222
      SR0.4304.6750.011
    • Table 3. Average color difference comparison under different light sources

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      Table 3. Average color difference comparison under different light sources

      DatasetMethodACD65D50
      Munsell-SGPCA1.3991.5281.5171.453
      SR0.2770.5010.4510.373
      SG-MunsellPCA6.2515.9725.9396.072
      SR0.2760.4850.4300.367
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    Xinyi Fang, Xiaoxia Wan, Shuo Shi, Xiao Teng, Junyan Yu. Multi-Spectral Color Data Dimension Reduction Model Research Based on Sparse Representation[J]. Laser & Optoelectronics Progress, 2021, 58(22): 2230003

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    Paper Information

    Category: Spectroscopy

    Received: Jan. 22, 2021

    Accepted: Feb. 12, 2021

    Published Online: Nov. 10, 2021

    The Author Email: Wan Xiaoxia (wan@whu.edu.cn)

    DOI:10.3788/LOP202158.2230003

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