Jian Zheng, Hao Liu, Xiangchun Yu, Chi Zheng. Image Exposure Correction Method Based on Inversion Fusion Framework[J]. Laser & Optoelectronics Progress, 2022, 59(12): 1210002
- Laser & Optoelectronics Progress
- Vol. 59, Issue 12, 1210002 (2022)
Fig. 1. Flow chart of proposed algorithm
Fig. 2. Contrast between the visual effects of the real haze map and the pseudo-fog map in an underexposed scene. (a) Initial image in an underexposed scene; (b) pseudo-fog map after intensity inversion; (c) real scene haze image
Fig. 3. Corresponding RGB pixel distribution of the pseudo-fog map and the real fog map. (a) The first column of Fig.2; (b) the second column of Fig.2; (c) the third column of Fig.2
Fig. 4. Image 1 comparison of experimental results of different exposure correction methods. (a) Original image; (b) RetinexNet algorithm; (c) MBLLEN algorithm; (d) DCP algorithm; (e) LIME algorithm; (f) proposed algorithm
Fig. 5. Image 2 comparison of experimental results of different exposure correction methods. (a) Original image; (b) RetinexNet algorithm; (c) MBLLEN algorithm; (d) DCP algorithm; (e) LIME algorithm; (f) proposed algorithm
Fig. 6. Image 3 comparison of experimental results of different exposure correction methods. (a) Original image; (b) RetinexNet algorithm; (c) MBLLEN algorithm; (d) DCP algorithm; (e) LIME algorithm; (f) proposed algorithm
Fig. 7. Image 4 comparison of experimental results of different exposure correction methods. (a) Original image; (b) RetinexNet algorithm; (c) MBLLEN algorithm; (d) DCP algorithm; (e) LIME algorithm; (f) proposed algorithm
Fig. 8. Comparison of NIQE mean value of correction results
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Table 1. Comparison of PSNR of each algorithm
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Table 2. Comparison of entropy of each algorithm
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Table 3. Comparison of AG of each algorithm
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