• Laser & Optoelectronics Progress
  • Vol. 58, Issue 14, 1410001 (2021)
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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    DOI: 10.3788/LOP202158.1410001 Cite this Article Set citation alerts
    Shikai Jin, Jiangtao Xu, Kaiming Nie. Low-Illumination Color Image Enhancement System Based on Single Sensor[J]. Laser & Optoelectronics Progress, 2021, 58(14): 1410001 Copy Citation Text show less
    Sensor spectral sensitivity. (a) SS of RGB+NIR CFA; (b) SS of CMYW CFA; (c) SS of CMYW subtraction
    Fig. 1. Sensor spectral sensitivity. (a) SS of RGB+NIR CFA; (b) SS of CMYW CFA; (c) SS of CMYW subtraction
    Image enhancement system architecture
    Fig. 2. Image enhancement system architecture
    Experimental environment. (a) Darkroom environment for image acquisition; (b) enlargement of some details
    Fig. 3. 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
    Fig. 4. 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
    Fig. 5. 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
    Fig. 6. 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
    Fig. 7. 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
    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 1. PSNR comparison of images processed by different noise reduction algorithms unit: dB
    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 2. Brightness mean values 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 3. Structural similarity comparison of three groups of images
    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
    Table 4. Comparison of PSNR of three groups of images unit: dB
    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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