Fast Removal of Non-uniform Camera Shake

Michael Hirsch

Christian J. Schuler

Stefan Harmeling

Bernhard Schölkopf
Proc. IEEE International Conference on Computer Vision 2011


Abstract
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.


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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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