Fast Removal of Non-uniform Camera Shake

Michael Hirsch

Christian J. Schuler

Stefan Harmeling

Bernhard Schölkopf
Proc. IEEE International Conference on Computer Vision 2011

Camera shake leads to non-uniform image blurs. State-of-the-art methods for removing camera shake model the blur as a linear combination of homographically transformed versions of the true image. While this is conceptually interesting, the resulting algorithms are computationally demanding. In this paper we develop a forward model based on the efficient filter flow framework, incorporating the particularities of camera shake, and show how an efficient algorithm for blur removal can be obtained. Comprehensive comparisons on a number of real-world blurry images show that our approach is not only substantially faster, but it also leads to better deblurring results.


Paper (pdf)Supplementary Material (zipped pdf)Poster (pdf)Talk Slides (pdf)Video of Talk at ICCV 2011

Example Images

• Comparison with Gupta et al., Single Image Deblurring Using Motion Density Functions, ECCV 2010.

Blurred image Xu et al., ECCV 2010 Gupta et al., ECCV 2010 Our approach

• Comparison with Harmeling et al., Space-Variant Single-Image Blind Deconvolution for Removing Camera Shake, NIPS 2010.

Blurred image Cho et al., SIGGRAPH 2009 Harmeling et al., NIPS 2010 Our approach

• Comparison with Joshi et al., Image deblurring using inertial measurement sensors, Siggraph 2010.

Blurred image Xu et al., ECCV 2010 Joshi et al., Siggraph 2010 Our approach

• Comparison with Whyte et al., Non-uniform Deblurring for Shaken Images, CVPR 2010.

Blurred image Fergus et al., Siggraph 2006 Whyte et al., CVPR 2010 Our approach


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