Conference Paper

E. W. Tramel and J. E. Fowler, “Video Compressed Sensing with Multihypothesis,” in Proceedings of the IEEE Data Compression Conference, J. A. Storer and M. W. Marcellin, Eds., Snowbird, UT, March 2011, pp. 193-202.

• Abstract:
  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.
• Text:

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