  This paper describes a coded aperture and keyed exposure approach to
compressive video measurement which admits a small physical platform, high
photon efficiency, high temporal resolution, and fast reconstruction
algorithms. The proposed projections satisfy the Restricted Isometry Property
(RIP), and hence compressed sensing theory provides theoretical guarantees on
the video reconstruction quality. Moreover, the projections can be easily
implemented using existing optical elements such as spatial light modulators
(SLMs). We extend these coded mask designs to novel dual-scale masks (DSMs)
which enable the recovery of a coarse-resolution estimate of the scene with
negligible computational cost. We develop fast numerical algorithms which
utilize both temporal correlations and optical flow in the video sequence as
well as the innovative structure of the projections. Our numerical experiments
demonstrate the efficacy of the proposed approach on short-wave infrared data.
