The DOI matches its Crossref record; 30 of the 30 references it cites were found in a registry or an index.
Unnatural L0 Sparse Representation for Natural Image Deblurring
Abstract
We show in this paper that the success of previous maximum a posterior (MAP) based blur removal methods partly stems from their respective intermediate steps, which implicitly or explicitly create an unnatural representation containing salient image structures. We propose a generalized and mathematically sound L0sparse expression, together with a new effective method, for motion deblurring. Our system does not require extra filtering during optimization and demonstrates fast energy decreasing, making a small number of iterations enough for convergence. It also provides a unified framework for both uniform and non-uniform motion deblurring. We extensively validate our method and show comparison with other approaches with respect to convergence speed, running time, and result quality.
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Cites
Blake, A., & Zisserman, A. (1987) · The MIT Press eBooks · doi:10.7551/mitpress/7132.001.0001 · Cited by 2,105
Removing camera shake from a single photograph
Fergus, R., Singh, B., Hertzmann, A., Roweis, S. T., & Freeman, W. T. (2006) · ACM Transactions on Graphics · doi:10.1145/1141911.1141956 · Cited by 1,815
High-quality motion deblurring from a single image
Shan, Q., Jia, J., & Agarwala, A. (2008) · ACM Transactions on Graphics · doi:10.1145/1360612.1360672 · Cited by 1,386
Self-citationUnderstanding and evaluating blind deconvolution algorithms
Levin, A., Weiss, Y., Durand, F., & Freeman, W. T. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206815 · Cited by 1,208
Fast Image Deconvolution using Hyper-Laplacian Priors
Krishnan, D., & Fergus, R. (2009) · Cited by 1,205
Blind deconvolution using a normalized sparsity measure
Krishnan, D., Tay, T., & Fergus, R. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995521 · Cited by 1,119
Two-Phase Kernel Estimation for Robust Motion Deblurring
Xu, L., & Jia, J. (2010) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-15549-9_12 · Cited by 1,027
Self-citationCho, S., & Lee, S. (2009) · ACM Transactions on Graphics · doi:10.1145/1618452.1618491 · Cited by 942
Image smoothing via L0gradient minimization
Xu, L., Lu, C., Xu, Y., & Jia, J. (2011) · Proceedings of the 2011 SIGGRAPH Asia Conference · doi:10.1145/2024156.2024208 · Cited by 873
Self-citationStructure extraction from texture via relative total variation
Xu, L., Yan, Q., Xia, Y., & Jia, J. (2012) · ACM Transactions on Graphics · doi:10.1145/2366145.2366158 · Cited by 867
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Multi-Stage Progressive Image Restoration
Zamir, S. W., Arora, A., Khan, S., Hayat, M., Khan, F. S., Yang, M.-H., & Shao, L. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr46437.2021.01458 · Cited by 2,095
Scale-Recurrent Network for Deep Image Deblurring
Tao, X., Gao, H., Shen, X., Wang, J., & Jia, J. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00853 · Cited by 1,316
Self-citationSchuler, C. J., Hirsch, M., Harmeling, S., & Schölkopf, B. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2481418 · Cited by 560
Dynamic Scene Deblurring Using Spatially Variant Recurrent Neural Networks
Zhang, J., Pan, J., Ren, J., Song, Y., Bao, L., Lau, R. W. H., & Yang, M.-H. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00267 · Cited by 384
DiffIR: Efficient Diffusion Model for Image Restoration
Xia, B., Zhang, Y., Wang, S., Wang, Y., Wu, X., Tian, Y., Yang, W., & Van Gool, L. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.01204 · Cited by 412
Metadata
- Authors
- Xu, L., Zheng, S., & Jia, J.
- Venue
- 2013 IEEE Conference on Computer Vision and Pattern Recognition
- Publisher
- IEEE
- Published
- 2013-06
- Pages
- 1107-1114
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2167307343
- Cited by
- 1,079
- References
- 30
- FWCI
- 39.47
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Xu, L., Zheng, S., & Jia, J. (2013). Unnatural L0 Sparse Representation for Natural Image Deblurring. 2013 IEEE Conference on Computer Vision and Pattern Recognition. https://doi.org/10.1109/cvpr.2013.147
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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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