The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Removing camera shake from a single photograph
Abstract
Camera shake during exposure leads to objectionable image blur and ruins many photographs. Conventional blind deconvolution methods typically assume frequency-domain constraints on images, or overly simplified parametric forms for the motion path during camera shake. Real camera motions can follow convoluted paths, and a spatial domain prior can better maintain visually salient image characteristics. We introduce a method to remove the effects of camera shake from seriously blurred images. The method assumes a uniform camera blur over the image and negligible in-plane camera rotation. In order to estimate the blur from the camera shake, the user must specify an image region without saturation effects. We show results for a variety of digital photographs taken from personal photo collections.
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Cites
Bayesian-Based Iterative Method of Image Restoration*
Richardson, W. H. (1972) · Journal of the Optical Society of America · doi:10.1364/josa.62.000055 · Cited by 4,160
An iterative technique for the rectification of observed distributions
Lucy, L. B. (1974) · The Astronomical Journal · doi:10.1086/111605 · Cited by 3,866
An Introduction to Variational Methods for Graphical Models
Jordan, M. I., Ghahramani, Z., Jaakkola, T. S., & Saul, L. K. (1999) · Machine Learning · doi:10.1023/a:1007665907178 · Cited by 3,791
Statistical Modeling of Photographic Images
Simoncelli, E. P. (2005) · Handbook of Image and Video Processing · doi:10.1016/b978-012119792-6/50089-9 · Cited by 93
Cited by
Image-to-Image Translation with Conditional Adversarial Networks
Isola, P., Zhu, J.-Y., Zhou, T., & Efros, A. A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.632 · Cited by 22,930
Nonlocally Centralized Sparse Representation for Image Restoration
Dong, W., Zhang, L., Shi, G., & Li, X. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2012.2235847 · Cited by 1,505
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
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
Self-citationBlind 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
Self-citation
Metadata
- Authors
- Fergus, R., Singh, B., Hertzmann, A., Roweis, S. T., & Freeman, W. T.
- Venue
- ACM Transactions on Graphics
- Published
- 2006-07
- Volume
- 25
- Issue
- 3
- Pages
- 787-794
- ISSN
- 0730-0301 (ISSN-L)
- 1557-7368
- OpenAlex
- W2098535678
- Cited by
- 1,815
- References
- 4
- FWCI
- 56.85
- Type
- journal article
- Language
- en
- Open access
- closed
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- Fergus, R., Singh, B., Hertzmann, A., Roweis, S. T., & Freeman, W. T. (2006). Removing camera shake from a single photograph. ACM Transactions on Graphics. https://doi.org/10.1145/1141911.1141956
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