Fast splitting algorithm for multiframe total variation blind video deconvolution
Applied Optics, Vol. 49, Issue 15, pp. 2761-2768 (2010)
http://dx.doi.org/10.1364/AO.49.002761
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Abstract
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
History
Original Manuscript: October 29, 2009
Revised Manuscript: March 30, 2010
Manuscript Accepted: April 1, 2010
Published: May 12, 2010
Citation
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)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-49-15-2761
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