The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
Image Deblurring via Extreme Channels Prior
Abstract
Camera motion introduces motion blur, affecting many computer vision tasks. Dark Channel Prior (DCP) helps the blind deblurring on scenes including natural, face, text, and low-illumination images. However, it has limitations and is less likely to support the kernel estimation while bright pixels dominate the input image. We observe that the bright pixels in the clear images are not likely to be bright after the blur process. Based on this observation, we first illustrate this phenomenon mathematically and define it as the Bright Channel Prior (BCP). Then, we propose a technique for deblurring such images which elevates the performance of existing motion deblurring algorithms. The proposed method takes advantage of both Bright and Dark Channel Prior. This joint prior is named as extreme channels prior and is crucial for achieving efficient restorations by leveraging both the bright and dark information. Extensive experimental results demonstrate that the proposed method is more robust and performs favorably against the state-of-the-art image deblurring methods on both synthesized and natural images.
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Cites
Single image haze removal using dark channel prior
He, K., Sun, J., & Tang, X. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2009.5206515 · Cited by 2,414
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
Understanding 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
Total variation blind deconvolution
Chan, T. F., & Wong, C.-K. (1998) · IEEE Transactions on Image Processing · doi:10.1109/83.661187 · Cited by 1,201
Multiscale Combinatorial Grouping
Arbelaez, P., Pont-Tuset, J., Barron, J., Marques, F., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.49 · Cited by 1,155
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
Unnatural L0 Sparse Representation for Natural Image Deblurring
Xu, L., Zheng, S., & Jia, J. (2013) · 2013 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2013.147 · Cited by 1,079
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
Cho, S., & Lee, S. (2009) · ACM Transactions on Graphics · doi:10.1145/1618452.1618491 · Cited by 942
Cited by
Bringing a Blurry Frame Alive at High Frame-Rate With an Event Camera
Pan, L., Scheerlinck, C., Yu, X., Hartley, R., Liu, M., & Dai, Y. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00698 · Cited by 308
Metadata
- Authors
- Yan, Y., Ren, W., Guo, Y., Wang, R., & Cao, X.
- Venue
- 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
- Publisher
- IEEE
- Published
- 2017-07
- Pages
- 6978-6986
- ISSN
- 1063-6919 (ISSN-L)
- OpenAlex
- W2740543610
- Cited by
- 365
- References
- 27
- FWCI
- 9.46
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Yan, Y., Ren, W., Guo, Y., Wang, R., & Cao, X. (2017). Image Deblurring via Extreme Channels Prior. 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). https://doi.org/10.1109/cvpr.2017.738
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