The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation
Abstract
We propose a weighted variational model to estimate both the reflectance and the illumination from an observed image. We show that, though it is widely adopted for ease of modeling, the log-transformed image for this task is not ideal. Based on the previous investigation of the logarithmic transformation, a new weighted variational model is proposed for better prior representation, which is imposed in the regularization terms. Different from conventional variational models, the proposed model can preserve the estimated reflectance with more details. Moreover, the proposed model can suppress noise to some extent. An alternating minimization scheme is adopted to solve the proposed model. Experimental results demonstrate the effectiveness of the proposed model with its algorithm. Compared with other variational methods, the proposed method yields comparable or better results on both subjective and objective assessments.
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Cites
Making a “Completely Blind” Image Quality Analyzer
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A multiscale retinex for bridging the gap between color images and the human observation of scenes
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The Retinex Theory of Color Vision
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Acquiring linear subspaces for face recognition under variable lighting
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An Iterative Regularization Method for Total Variation-Based Image Restoration
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Naturalness Preserved Enhancement Algorithm for Non-Uniform Illumination Images
Wang, S., Zheng, J., Hu, H.-M., & Li, B. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2013.2261309 · Cited by 1,755
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Self-citationDetermining lightness from an image
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Cited by
LIME: Low-Light Image Enhancement via Illumination Map Estimation
Guo, X., Li, Y., & Ling, H. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2639450 · Cited by 2,998
EnlightenGAN: Deep Light Enhancement Without Paired Supervision
Jiang, Y., Gong, X., Liu, D., Cheng, Y., Fang, C., Shen, X., Yang, J., Zhou, P., & Wang, Z. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3051462 · Cited by 2,715
Structure-Revealing Low-Light Image Enhancement Via Robust Retinex Model
Li, M., Liu, J., Yang, W., Sun, X., & Guo, Z. (2018) · IEEE Transactions on Image Processing · doi:10.1109/tip.2018.2810539 · Cited by 1,245
SNR-Aware Low-light Image Enhancement
Xu, X., Wang, R., Fu, C.-W., & Jia, J. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01719 · Cited by 688
Low-Light Image Enhancement with Normalizing Flow
Wang, Y., Wan, R., Yang, W., Li, H., Chau, L.-P., & Kot, A. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v36i3.20162 · Cited by 533
Metadata
- Authors
- Fu, X., Zeng, D., Huang, Y., Zhang, X.-P., & Ding, X.
- Venue
- 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2016-06
- Volume
- 2016
- Pages
- 2782-2790
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2468596194
- Cited by
- 1,081
- References
- 24
- FWCI
- 13.51
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Fu, X., Zeng, D., Huang, Y., Zhang, X.-P., & Ding, X. (2016). A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr.2016.304
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