A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion
Abstract
:1. Introduction
2. Related Work
3. Proposed Method
3.1. Brightness Transformation Function
3.2. Weights Definition
3.3. Pyramid Fusion
Algorithm 1: The proposed algorithm |
Input: Source image I, parameter a, parameter n |
output: The result after fusion |
1: Calculate , by Equation (5); |
2: Put , into the Laplace pyramid; |
3: Take image as the source image for calculating the weight map W; |
4: Put W into the Gaussian pyramid; |
5: for each , and do |
6: Calculate by Equation (13); |
7: end for |
8: Use Laplacian pyramid reconstruction to obtain the final fused image . |
4. Experiment and Analysis
4.1. Subjective Evaluation of Experimental Results
4.2. Objective Assessment of Image Quality
4.2.1. Lightness Order Error (LOE)
4.2.2. Visual Information Fidelity
4.2.3. Natural Image Quality Evaluator
5. Discussion
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Input | Dong | LIME | MSR | MF | NPE | SRIE | Ours |
---|---|---|---|---|---|---|---|
bookshelf | 961.8 | 1063.3 | 1942.6 | 563.3 | 810.3 | 608.2 | 358.2 |
cupboard | 306.9 | 431.4 | 930.6 | 368.4 | 678.3 | 348.9 | 361.9 |
doll | 449.9 | 645.1 | 1534.8 | 397.2 | 800.5 | 476.8 | 365.5 |
classroom | 470.6 | 687.7 | 1636.5 | 598.1 | 1120.9 | 539.7 | 410.3 |
swimming pool | 1244.6 | 538.2 | 1373.6 | 684.5 | 1875.2 | 1140.9 | 295.5 |
hall | 805.6 | 622.1 | 1638.9 | 658.9 | 1698.9 | 801.1 | 280.7 |
gym | 625.8 | 846.9 | 1742.8 | 533.3 | 1014.2 | 666.2 | 392.1 |
wardrobe | 574.3 | 1211.5 | 2477.9 | 613.3 | 554.2 | 429.5 | 455.2 |
Input | Dong | LIME | MSR | MF | NPE | SRIE | Ours |
---|---|---|---|---|---|---|---|
bookshelf | 9.734 | 18.763 | 16.214 | 7.199 | 8.374 | 4.908 | 11.533 |
cupboard | 35.375 | 82.298 | 89.709 | 42.794 | 54.187 | 14.187 | 63.57 |
doll | 41.627 | 146.493 | 165.138 | 59.936 | 63.301 | 16.742 | 66.871 |
classroom | 42.835 | 125.786 | 137.805 | 55.984 | 85.473 | 16.337 | 95.942 |
swimming pool | 9.256 | 23.655 | 19.558 | 9.109 | 13.393 | 4.373 | 15.948 |
hall | 8.537 | 18.114 | 14.541 | 8.858 | 9.876 | 4.361 | 10.375 |
gym | 23.621 | 84.685 | 70.673 | 30.145 | 48.797 | 9.566 | 54.606 |
wardrobe | 22.204 | 42.362 | 36.703 | 16.675 | 22.063 | 9.233 | 31.02 |
Input | Dong | LIME | MSR | MF | NPE | SRIE | Ours |
---|---|---|---|---|---|---|---|
bookshelf | 8.331 | 9.002 | 8.059 | 8.704 | 9.018 | 7.769 | 7.081 |
cupboard | 11.372 | 10.927 | 10.998 | 12.932 | 11.566 | 10.224 | 10.128 |
doll | 7.653 | 8.085 | 8.536 | 8.389 | 8.106 | 7.741 | 7.588 |
classroom | 10.714 | 11.547 | 10.322 | 11.485 | 11.485 | 10.771 | 10.153 |
swimming pool | 9.913 | 9.247 | 8.864 | 9.585 | 9.264 | 8.501 | 8.438 |
hall | 10.703 | 11.119 | 9.788 | 11.919 | 10.272 | 9.922 | 9.673 |
gym | 8.885 | 8.509 | 8.232 | 9.843 | 8.314 | 7.652 | 7.145 |
wardrobe | 6.965 | 7.412 | 6.762 | 7.805 | 7.209 | 6.423 | 5.782 |
Method | DICM | LIME | VV | Avg. |
---|---|---|---|---|
Dong [13] | 4.313 | 2.601 | 3.597 | 3.504 |
LIME [14] | 3.421 | 2.636 | 3.561 | 3.206 |
MSR [12] | 3.346 | 2.452 | 3.629 | 3.142 |
MF [17] | 3.506 | 2.825 | 3.234 | 3.188 |
NPE [15] | 3.277 | 2.562 | 3.191 | 3.024 |
SRIE [16] | 3.556 | 2.541 | 3.454 | 3.183 |
Ours | 3.121 | 2.235 | 3.152 | 2.836 |
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Zhang, E.; Guo, L.; Guo, J.; Yan, S.; Li, X.; Kong, L. A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion. Appl. Sci. 2023, 13, 10230. https://doi.org/10.3390/app131810230
Zhang E, Guo L, Guo J, Yan S, Li X, Kong L. A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion. Applied Sciences. 2023; 13(18):10230. https://doi.org/10.3390/app131810230
Chicago/Turabian StyleZhang, Enqi, Lihong Guo, Junda Guo, Shufeng Yan, Xiangyang Li, and Lingsheng Kong. 2023. "A Low-Brightness Image Enhancement Algorithm Based on Multi-Scale Fusion" Applied Sciences 13, no. 18: 10230. https://doi.org/10.3390/app131810230