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Decomposition of images by the anisotropic Rudin‐Osher‐Fatemi model
Abstract
The total‐variation‐based image denoising model of Rudin, Osher, and Fatemi can be generalized in a natural way to favor certain edge directions. We consider the resulting anisotropic energies and study properties of their minimizers. © 2004 Wiley Periodicals, Inc.
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Cited by
An Iterative Regularization Method for Total Variation-Based Image Restoration
Osher, S., Burger, M., Goldfarb, D., Xu, J., & Yin, W. (2005) · Multiscale Modeling & Simulation · doi:10.1137/040605412 · Cited by 1,787
Self-citationNon-local Color Image Denoising with Convolutional Neural Networks
Lefkimmiatis, S. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.623 · Cited by 363
Metadata
- Authors
- Esedoḡlu, S., & Osher, S. J.
- Venue
- Communications on Pure and Applied Mathematics
- Publisher
- Wiley
- Published
- 2004-09-27
- Volume
- 57
- Issue
- 12
- Pages
- 1609-1626
- ISSN
- 0010-3640 (ISSN-L)
- 1097-0312
- OpenAlex
- W2084115655
- Cited by
- 223
- References
- 0
- FWCI
- 5.09
- Type
- journal article
- Language
- en
- Open access
- closed
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- Esedoḡlu, S., & Osher, S. J. (2004). Decomposition of images by the anisotropic Rudin‐Osher‐Fatemi model. Communications on Pure and Applied Mathematics. https://doi.org/10.1002/cpa.20045
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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