Invertible Motion Blur in Video
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Amit
Agrawal, Yi Xu and Ramesh Raskar ACM SIGGRAPH 2009 |
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Linear motion-blur in a
single photo is
non-invertible but we make the blur in video invertible by changing
the exposure time of successive frames. We show an automatic deblurring
approach without special camera hardware by creating jointly invertible
PSF, estimating PSF and segmenting moving objects on non-uniform
background.
Abstract We show that motion blur in
successive video frames is
invertible even
if the point-spread function (PSF) due to motion smear in a single
photo is non-invertible. Blurred photos exhibit nulls (zeros) in the
frequency transform of the PSF, leading to an ill-posed deconvolution.
Hardware solutions to avoid this require specialized devices such as
the coded exposure camera or accelerating sensor motion. We employ
ordinary video cameras and introduce the notion of null-filling along
with joint-invertibility of multiple blur-functions. The key idea is to
record the same object with varying PSFs, so that the nulls in the
frequency component of one frame can be filled by other frames. The
combined frequency transform becomes null-free, making deblurring
well-posed. We achieve jointly-invertible blur simply by changing the
exposure time of successive frames. We address the problem of automatic
deblurring of objects moving with constant velocity by solving the four
critical components: preservation of all spatial frequencies,
segmentation of moving parts, motion estimation of moving parts, and
non-degradation of the static parts of the scene. We demonstrate
several challenging cases of object motion blur including textured
backgrounds and partial occluders. |
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Paper (Preprint) pdf
(13 MB) Video (Quicktime, 41 MB) SIGGRAPH 2009 Talk (ppt, 67 MB)
Related Papers in Motion/Focus Deblurring SIGGRAPH 2006 Coded exposure for motion deblurring CVPR 2007
Simultaneous motion
deblurring and super-resolution
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