Multimedia acquisition and coding techniques have received increasing attention due to the wide spread of multimedia telecommunication. Compressed Sensing (CS) is an emerging signal processing technology that enables acquisition of signals that exhibit sparsity in some basis, directly in a compressed manner. CS proves to be powerful for energy constrained devices that benefit from processing at lower sampling rates. In this paper, we propose a compressed sensing framework for images and video signals that relies on an efficient perceptual-based weighting strategy. The proposed compressed sensing strategy focuses the measurements and recovery on the most perceptually pronounced coefficients of the underlying signal. Simulation results demonstrate that the proposed framework provides significant improvement over different CS systems.