Laser & Optoelectronics Progress, Volume. 58, Issue 14, 1410001(2021)

Low-Illumination Color Image Enhancement System Based on Single Sensor

Shikai Jin1,2, Jiangtao Xu1,2、*, and Kaiming Nie1,2
Author Affiliations
  • 1School of Microelectronics, Tianjin University, Tianjin 300072, China
  • 2Key Laboratory of Imaging and Sensing Microelectronics Technology, Tianjin 300072, China
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    Figures & Tables(11)
    Sensor spectral sensitivity. (a) SS of RGB+NIR CFA; (b) SS of CMYW CFA; (c) SS of CMYW subtraction
    Image enhancement system architecture
    Experimental environment. (a) Darkroom environment for image acquisition; (b) enlargement of some details
    Comparison of noise reduction effects for different algorithms. (a) Difference; (b) BF; (c) JBF; (d) NLM; (e) INLM; (f) Joint NLM
    First group of images in different environments and images processed by different algorithms. (a) Image without NIR under normal illumination; (b) image without NIR under low illumination; (c) image with NIR under low illumination; (d) low illumination image processed by system in Ref. [11]; (e) low illumination image processed by system in Ref. [14]; (f) low illumination image processed by proposed system
    Second group of images in different environments and images processed by different algorithms. (a) Image without NIR under normal illumination; (b) image without NIR under low illumination; (c) image with NIR under low illumination; (d) low illumination image processed by system in Ref. [11]; (e) low illumination image processed by system in Ref. [14]; (f) low illumination image processed by proposed system
    Third group of images in different environments and images processed by different algorithms. (a) Image without NIR under normal illumination; (b) image without NIR under low illumination; (c) image with NIR under low illumination; (d) low illumination image processed by system in Ref. [11]; (e) low illumination image processed by system in Ref. [14]; (f) low illumination image processed by proposed system
    • Table 1. PSNR comparison of images processed by different noise reduction algorithms unit: dB

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      Table 1. PSNR comparison of images processed by different noise reduction algorithms unit: dB

      AlgorithmRGB
      Originalimage18.16118.12516.580
      Ref.[17]18.53018.47516.657
      Ref.[21]19.17119.13117.157
      Ref.[22]19.10219.06417.061
      Ref.[23]19.13119.11317.126
      Ours19.33919.28417.857
    • Table 2. Brightness mean values comparison of three groups of images

      View table

      Table 2. Brightness mean values comparison of three groups of images

      Image(b)(c)(d)(e)(f)
      Fig. 5251.814267.478237.167245.263267.583
      Fig. 6250.962266.593236.281244.384266.675
      Fig. 7246.589264.837233.893241.765264.951
    • Table 3. Structural similarity comparison of three groups of images

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      Table 3. Structural similarity comparison of three groups of images

      Image(b)(c)(d)(e)(f)
      Fig. 50.7010.7480.6890.7320.749
      Fig. 60.7020.7460.6920.7310.747
      Fig. 70.6980.7450.6880.7300.746
    • Table 4. Comparison of PSNR of three groups of images unit: dB

      View table

      Table 4. Comparison of PSNR of three groups of images unit: dB

      Image(b)(c)(d)(e)(f)
      Fig. 519.78020.28019.96419.25620.501
      Fig. 619.65320.26719.84819.24920.384
      Fig. 719.42120.17819.66519.15820.296
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    Shikai Jin, Jiangtao Xu, Kaiming Nie. Low-Illumination Color Image Enhancement System Based on Single Sensor[J]. Laser & Optoelectronics Progress, 2021, 58(14): 1410001

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    Paper Information

    Category: Image Processing

    Received: Oct. 10, 2020

    Accepted: Nov. 14, 2020

    Published Online: Jul. 6, 2021

    The Author Email: Xu Jiangtao (xujiangtao@tju.edu.cn)

    DOI:10.3788/LOP202158.1410001

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