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Applied Optics

Applied Optics


  • Editor: Joseph N. Mait
  • Vol. 49, Iss. 15 — May. 20, 2010
  • pp: 2761–2768

Fast splitting algorithm for multiframe total variation blind video deconvolution

You-Wei Wen, Chaoqiang Liu, and Andy M. Yip  »View Author Affiliations

Applied Optics, Vol. 49, Issue 15, pp. 2761-2768 (2010)

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We consider the recovery of degraded videos without complete knowledge about the degradation. A spatially shift-invariant but temporally shift-varying video formation model is used. This leads to a simple multiframe degradation model that relates each original video frame with multiple observed frames and point spread functions (PSFs). We propose a variational method that simultaneously reconstructs each video frame and the associated PSFs from the corresponding observed frames. Total variation (TV) regularization is used on both the video frames and the PSFs to further reduce the ill-posedness and to better preserve edges. In order to make TV minimization practical for video sequences, we propose an efficient splitting method that generalizes some recent fast single-image TV minimization methods to the multiframe case. Both synthetic and real videos are used to show the performance of the proposed method.

© 2010 Optical Society of America

OCIS Codes
(100.3020) Image processing : Image reconstruction-restoration
(150.1135) Machine vision : Algorithms
(100.1455) Image processing : Blind deconvolution
(110.4155) Imaging systems : Multiframe image processing

ToC Category:
Image Processing

Original Manuscript: October 29, 2009
Revised Manuscript: March 30, 2010
Manuscript Accepted: April 1, 2010
Published: May 12, 2010

You-Wei Wen, Chaoqiang Liu, and Andy M. Yip, "Fast splitting algorithm for multiframe total variation blind video deconvolution," Appl. Opt. 49, 2761-2768 (2010)

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