Coded Exposure Deblurring: Optimized Codes for
PSF Estimation and Invertibility

 
Amit Agrawal and Yi Xu
CVPR 2009


Abstract


We consider the problem of single image object motion deblurring from a static camera. It is well-known that deblurring of moving objects using a traditional camera is ill posed, due to the loss of high spatial frequencies in the captured blurred image. A coded exposure camera modulates the integration pattern of light by opening and closing the shutter within the exposure time using a binary code. The code is chosen to make the resulting point spread function (PSF) invertible, for best deconvolution performance. However, for a successful deconvolution algorithm, PSF estimation is as important as PSF invertibility. We show that PSF estimation is easier if the resulting motion blur is smooth and the optimal code for PSF invertibility could worsen PSF estimation, since it leads to non-smooth blur.


We show that both criterions of PSF invertibility and PSF estimation can be simultaneously met, albeit with a slight increase in the deconvolution noise. We propose design rules for a code to have good PSF estimation capability and outline two search criteria for finding the optimal code for a given length. We present theoretical analysis comparing the performance of the proposed code with the code optimized solely for PSF invertibility. We also show how to easily implement coded exposure on a consumer grade machine vision camera with no additional hardware. Real experimental results demonstrate the effectiveness of the proposed codes for motion deblurring.

Paper (Preprint)


High res pdf,    Low res pdf


Motion Blur Datasets and Matlab/C codes


Related Papers in Motion/Focus Deblurring

SIGGRAPH 2006      Coded exposure for motion deblurring
SIGGRAPH 2007      Coded aperture and a new theory of light field capture
SIGGRAPH 2009      Invertible Motion Blur in Video

CVPR 2007              Simultaneous motion deblurring and super-resolution
CVPR 2009              Optimal Single Image Capture for Motion Deblurring









In Levin et al 2007, codes for coded aperture were proposed that help in discriminating depth by inserting zeros in the frequency spectrum. Thus, PSF invertibility was intentionally sacrificed to achieve PSF estimation. Inserting zeros in frequency spectrum makes deconvolution more difficult, challenging and susceptible to noise, and thus require image priors/training etc. to constrain the deblurred output. In this paper, we show that one does not need to sacrifice PSF invertibility to obtain codes that help in PSF estimation. Both can be simultaneously achieved by a careful choice of the code. Our approach does not use any image priors or training set.



References

1. A. Levin, R. Fergus, F. Durand, W. T. Freeman. Image and Depth from a Conventional Camera with a Coded Aperture. SIGGRAPH 2007
2. Ashok Veeraraghavan, Ramesh Raskar, Amit Agrawal, Ankit Mohan and Jack Tumblin. Dappled Photography: Mask Enhanced Cameras for Heterodyned Light Fields and Coded Aperture Refocusing, SIGGRAPH 2007
3. Ramesh Raskar, Amit Agrawal and Jack Tumblin, Coded Exposure Photography: Motion Deblurring using Fluttered Shutter, SIGGRAPH 2006
 

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