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Abstract
Motion blur removal from images sometimes need to estimate spatially-varying point spread functions (PSFs). We address two critical problems in this process.
Our framework applies to general single-image and stereo-image spatially-varying deblurring.
Downloads
|   | "Depth-Aware Motion Deblurring" Li Xu and Jiaya Jia IEEE International Conference on Computational Photography (ICCP), 2012  [Paper (pdf, 
4.6MB)]  [Presentation 
Slides] | 
Our Deblurring Work
 Large-Kernel Robust Motion Deblurring
Large-Kernel Robust Motion Deblurring
 High-Quality Iterative Optimization
High-Quality Iterative Optimization
More Examples
Stereopsis Deblurring
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| Left Image | Right Image | Blur Removed Image (Left) | Blur Removed Image (Right) | 
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| Left Image | Right Image | Blur Removed Image (Left) | Xu and Jia ECCV 10 | 
Spatially-Varying Deblurring
References
[1] L. Xu, J. Jia, Two-phase Kernel Estimation for Robust Motion Deblurring, ECCV 2010
[1] O. Whyte, J. Sivic, A. Zisserman, and J. Ponce, Non-uniform Deblurring for Shaken Images, CVPR 2010
[2] N. Joshi, S.B. Kang, L. Zitnick, and R. Szeliski, Image Deblurring with Inertial Measurement Sensors. ACM SIGGRAPH 2010
[3] A. Gupta, N. Joshi, L. Zitnick, M. Cohen, and B. Curless, Single Image Deblurring Using Motion Density Functions, ECCV 2010