A new framework based on sparse representation applied to monitor video

A new framework is proposed for compressed sensing (CS) video application, in which the dictionary can be trained based on traditional dictionary algorithms to unify computational complexity and reconstruction accuracy. In the new framework, a forgetting factor is employed for adjacent frames such that the trade off between the complexity and the performance can be considered. Simulation results show that the proposed framework achieves a better performance than traditional approaches.