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2011
IEEE

Video Compressed Sensing with Multihypothesis

8 years 2 months ago
Video Compressed Sensing with Multihypothesis
The compressed-sensing recovery of video sequences driven by multihypothesis predictions is considered. Specifically, multihypothesis predictions of the current frame are used to generate a residual in the domain of the compressed-sensing random projections. This residual being typically more compressible than the original frame leads to improved reconstruction quality. To appropriately weight the hypothesis predictions, a Tikhonov regularization to an ill-posed least-squares optimization is proposed. This method is shown to outperform both recovery of the frame independently of the others as well as recovery based on single-hypothesis prediction.
Eric W. Tramel, James E. Fowler
Added 14 May 2011
Updated 14 May 2011
Type Journal
Year 2011
Where DCC
Authors Eric W. Tramel, James E. Fowler
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