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An Algorithm for Total Variation Minimization and Applications
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Citations
Cited by
A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging
Chambolle, A., & Pock, T. (2011) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-010-0251-1 · Cited by 4,336
Self-citationLearning Deep CNN Denoiser Prior for Image Restoration
Zhang, K., Zuo, W., Gu, S., & Zhang, L. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.300 · Cited by 2,116
A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
Wang, Y., Yang, J., Yin, W., & Zhang, Y. (2008) · SIAM Journal on Imaging Sciences · doi:10.1137/080724265 · Cited by 1,975
A Duality Based Approach for Realtime TV-L 1 Optical Flow
Zach, C., Pock, T., & Bischof, H. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-74936-3_22 · Cited by 1,658
Fast Image Recovery Using Variable Splitting and Constrained Optimization
Afonso, M. V., Bioucas-Dias, J. M., & Figueiredo, M. A. T. (2010) · IEEE Transactions on Image Processing · doi:10.1109/tip.2010.2047910 · Cited by 1,223
Metadata
- Authors
- Chambolle, A.
- Venue
- Journal of Mathematical Imaging and Vision
- Published
- 2004-01
- Volume
- 20
- Issue
- 1-2
- Pages
- 89-97
- ISSN
- 0924-9907 (ISSN-L)
- 1573-7683
- OpenAlex
- W2144275666
- Cited by
- 832
- References
- 0
- FWCI
- 12.57
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: An Algorithm for Total Variation Minimization and Applications. https://app.cochat.ai/papers/10.1023/b:jmiv.0000011325.36760.1e
- The paper
- Chambolle, A. (2004). An Algorithm for Total Variation Minimization and Applications. Journal of Mathematical Imaging and Vision. https://doi.org/10.1023/b%3Ajmiv.0000011325.36760.1e
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.