  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.
