Ruoyou Wu, Dexing Wang, Hongchun Yuan, Peng Gong, Guanqi Chen, Dan Wang. Low-Light Image Enhancement Based on Multi-Branch All Convolutional Neural Network[J]. Laser & Optoelectronics Progress, 2020, 57(14): 141021
- Laser & Optoelectronics Progress
- Vol. 57, Issue 14, 141021 (2020)
Fig. 1. Structure of convolutional block attention module
Fig. 2. Architecture of multi-branch all convolutional neural network
Fig. 3. Noise extraction module
Fig. 4. Subjective visual comparison of synthetic low-light images without noise. (a) Image of parrots; (b) image of building2; (c) image of buildings; (d) image of monarch
Fig. 5. Subjective visual comparison of synthetic low-light images with noise. (a) Image of parrots; (b) image of building2; (c) image of buildings; (d) image of monarch
Fig. 6. Subjective visual comparison of real low-light images. (a)(b) Images from LIME dataset; (c)(d) images from DICM dataset; (e) image from MEF dataset
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Table 1. Comparison of objective evaluation indicators for synthetic low-light images without noise
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Table 2. Comparison of objective evaluation indicators for synthetic low-light images with noise
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Table 3. Comparison of objective evaluation indicators for real low-light images
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Table 4. Algorithm processing time comparison
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