Gyro-based multi-image deconvolution for removing handshake blur

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 3366-3373

  Park, Sung Hee ^a   Levoy, Marc ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CAMERAS; GYROSCOPES; PATTERN RECOGNITION;

CAMERA CONTROLS; CAMERA MOTIONS; EFFECTIVENESS AND EFFICIENCIES; IMAGE DEBLURRING; MOBILE CAMERA; MULTIPLE-FRAME; NATURAL SCENES; RESOLUTION IMAGERY;

IMAGE ENHANCEMENT;

EID: 84911378082     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.430     Document Type: Conference Paper

References (9)

1. G. Boracchi and A. Foi. Modeling the performance of image restoration from motion blur. TIP, 21(8):3502-3517, 2012.
2. S. W. Hasinoff, F. Durand, and W. T. Freeman. Noise-optimal capture for high dynamic range photography. In CVPR, 2010.
3. N. Joshi, S. B. Kang, C. L. Zitnick, and R. Szeliski. Image de-blurring using inertial measurement sensors. In SIGGRAPH, 2010.
4. A. Karpenko, D. Jacobs, J. Baek, and M. Levoy. Digital video stabilization and rolling shutter correction using gyroscopes. CSTR 2011-03, Stanford University, CS, 2011.
5. A. Levin, R. Fergus, F. Durand, and W. T. Freeman. Decon-volution using natural image priors. MIT CSAIL, 2007.
6. S. H. Park and M. Levoy. Handling moving objects and over-exposed regions in non-blind multi-image deconvolu-tion. Stanford Computer Graphics Laboratory Technical Report, 2014.
7. O. Whyte, J. Sivic, A. Zisserman, and J. Ponce. Non-uniform deblurring for shaken images. IJCV, 98(2):168-186, 2012.
8. N. Wiener. Extrapolation, Interpolation, and Smoothing of Stationary Time Series. MIT press, 1964.
9. L. Zhang, A. Deshpande, and X. Chen. Denoising vs. de-blurring: Hdr imaging techniques using moving cameras. In CVPR, 2010.