Kui Wang, Fuzhen Huang. Multiscale Retinex Image Enhancement in HSV Space Based on Illumination Compensation[J]. Laser & Optoelectronics Progress, 2022, 59(10): 1010004
- Laser & Optoelectronics Progress
- Vol. 59, Issue 10, 1010004 (2022)
Fig. 1. Flowchart of proposed algorithm
Fig. 2. Illumination estimation results of intrinsic protrusion layer. (a) Intrinsic protrusion layer; (b) GKF; (c) BKF; (d) IBKF
Fig. 3. Reflection layer obtained by intrinsic protrusion layer. (a) Intrinsic protrusion layer; (b) GKF; (c) BKF; （d） IBKF
Fig. 4. Bilateral Gamma curves
Fig. 5. Illumination compensation layer and brightness transition layer obtained by different φ values.
Fig. 6. Gray histograms corresponding to different brightness transition layers and illumination compensation layer. (a) Illumination compensation layer; (b) φ=0.3; (c) φ=0.5; (d) φ=0.8
Fig. 7. Comparison of convergence curves before and after sparrow search improvement. （a） Before disturbance； （b） after disturbance
Fig. 8. Illumination compensation of reflection layer. (a) Brightness transition layer; (b) illumination layer; (c) reflection layer; (d) illumination compensation result
Fig. 9. Comparison of results before and after illumination compensation. (a) Original image; (b) RES1; (c) RES2; (d) proposed algorithm
Fig. 10. Comparison of results before and after adaptation. (a) RES3; (b) RES4; (c) RES5; (d) proposed algorithm
Fig. 11. Low illumination image enhancement results under natural light source obtained by different algorithms. (a) Original images; (b) SSR; (c) MSR; (d) MSRCR; (e) method in Ref. [11]; (f) method in Ref. [12];(g) method in Ref. [13]; (h) proposed algorithm
Fig. 12. Low illumination image enhancement results under artificial light source obtained by different algorithms. (a) Original images; (b) SSR; (c) MSR; (d) MSRCR; (e) method in Ref. [11]; (f) method in Ref. [12]; (g) method in Ref. [13]; (h) proposed algorithm
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Table 1. Quality assessment results of reflection layer
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Table 2. Quality assessment of synthetic results
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Table 3. Quality evaluation of low illumination image enhancement results under natural light source by different algorithms
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Table 4. Quality evaluation of low illumination image enhancement results under artificial light source by different algorithms
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