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Tree-Structure Bayesian Compressive Sensing for Video

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arxiv 1410.3080 v1 pith:HMY24OQW submitted 2014-10-12 cs.CV

classification cs.CV
keywords compressivebayesiansensingvideoalgorithmcoloradoptedaperture
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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.

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    Random data sketching lets Bayesian varying coefficient regression run on compressed data with posterior contraction and nearly equivalent predictive performance to the uncompressed model.

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