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    Journals >Laser & Optoelectronics Progress >Volume 59 >Issue 14 >Page 1415029 > Article
    • Laser & Optoelectronics Progress
    • Vol. 59, Issue 14, 1415029 (2022)
    High Dynamic Range Imaging Method Based on YCbCr Color Space Fusion
    Lu Tang1, Rongsheng Lu1,*, Yanqiong Shi2, and Haibing Hu1
    Author Affiliations
  • 1College of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Hefei 230009, Anhui , China
  • 2College of Mechanical and Electrical Engineering, Anhui Jianzhu University, Hefei 230022, Anhui , China
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    DOI: 10.3788/LOP202259.1415029 Cite this Article Set citation alerts
    Lu Tang, Rongsheng Lu, Yanqiong Shi, Haibing Hu. High Dynamic Range Imaging Method Based on YCbCr Color Space Fusion[J]. Laser & Optoelectronics Progress, 2022, 59(14): 1415029 Copy Citation Text show less
    Multi-resolution fusion algorithm flow based on YCbCr color space
    Fig. 1. Multi-resolution fusion algorithm flow based on YCbCr color space
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    Y-channel multi-resolution weighted fusion process
    Fig. 2. Y-channel multi-resolution weighted fusion process
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    Fusion results of different algorithms of “Venice” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
    Fig. 3. Fusion results of different algorithms of “Venice” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
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    Fusion results of different algorithms of “Fountain” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
    Fig. 4. Fusion results of different algorithms of “Fountain” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
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    Fusion results of different algorithms of “Outdoor” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
    Fig. 5. Fusion results of different algorithms of “Outdoor” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
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    Fusion results of different algorithms of “Indoor scene” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
    Fig. 6. Fusion results of different algorithms of “Indoor scene” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
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    Fusion results of different algorithms of “Outdoor scene” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
    Fig. 7. Fusion results of different algorithms of “Outdoor scene” image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) Guided Filtering; (d) Gradient Domain; (e) Adaptive Weights; (f) DSIFT-GF; (g) proposed algorithm
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    Fusion results of focus stacking image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) proposed algorithm
    Fig. 8. Fusion results of focus stacking image sequence. (a) Input image sequence; (b) Mertens’ algorithm; (c) proposed algorithm
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    Objective evaluation of multi-exposure images fusion results
    Fig. 9. Objective evaluation of multi-exposure images fusion results
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    Objective evaluation graph of fusion results of focus stacking image
    Fig. 10. Objective evaluation graph of fusion results of focus stacking image
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    ScoreQuality scaleHinder scale
    1Very badHinder viewing very seriously
    2BadHinder viewing
    3GeneralCan clearly see the change of image quality and hinder viewing very slightly
    4Good

    Can see the change of image quality but does not hinder viewing

    No picture quality change at all

    5Very Good
    Table 1. Subjective scoring criteria
    Objective evaluation indexMertens’ algorithmProposed algorithm
    Standard deviation33.565957.3815
    Average gradient1.06914.7621
    Information entropy6.38027.2109
    Spatial frequency2.423610.3741
    Table 2. Objective evaluation table of fusion results of focus stacking image
    Abstract
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    Equations (35)
    References (24)
    Cited By (4)
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    Lu Tang, Rongsheng Lu, Yanqiong Shi, Haibing Hu. High Dynamic Range Imaging Method Based on YCbCr Color Space Fusion[J]. Laser & Optoelectronics Progress, 2022, 59(14): 1415029
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    Paper Information
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