Tree-Structure Bayesian Compressive Sensing for Video

Xin Yuan, Patrick Llull, David J. Brady, Lawrence Carin

Research output: Contribution to journalArticlepeer-review

Abstract

A Bayesian compressive sensing framework is developed for video reconstruction based on the color coded aperture compressive temporal imaging (CACTI) system. By exploiting the three dimension (3D) tree structure of the wavelet and Discrete Cosine Transformation (DCT) coefficients, a Bayesian compressive sensing inversion algorithm is derived to reconstruct (up to 22) color video frames from a single monochromatic compressive measurement. Both simulated and real datasets are adopted to verify the performance of the proposed algorithm.
Original languageUndefined/Unknown
JournalArxiv preprint
StatePublished - Oct 12 2014
Externally publishedYes

Keywords

  • cs.CV

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