Computer Vision Approach for Visibility Enhancement of Dull Images
Author:
Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-1677-9_4
Reference15 articles.
1. Shi, Z., Zhu, M., Guo, B., Zhao, M., Zhang, C.: Nighttime low illumination image enhancement with single image using bright/dark channel prior. EURASIP J. Image Video Process. 2018(1), 1–15 (2018). https://doi.org/10.1186/s13640-018-0251-4
2. Wang, W., Wu, X., Yuan, X., Gao, Z.: An experiment-based review of low-light image enhancement methods. IEEE Access 8, 87884–87917 (2020)
3. Yu, S.-Y., Zhu, H.: Low-illumination image enhancement algorithm based on a physical lighting model. IEEE Trans. Circ. Syst. Video Technol. 29(1), 28–37 (2017)
4. Guo, X., Li, Y., Ling, H.: LIME: low-light image enhancement via illumination map estimation. IEEE Trans. Image Process. 26(2), 982–993 (2016)
5. Zhou, Z., Sang, N., Hu, X.: Global brightness and local contrast adaptive enhancement for low illumination color image. Optik 125(6), 1795–1799 (2014)
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