Perceptually weighted compressed sensing for video acquisition

Abstract

Efficient video acquisition and coding techniques have received increasing attention due to the wide spread of multimedia telecommunication. Compressed Sensing (CS) is an emerging technology, which enables acquiring video in a compressed manner. CS proves to be very powerful for energy constrained devices that benefit from processing at lower sampling rates. In this paper, a framework for compressed video sensing (CVS) that relies on an efficient fixed perceptual weighting strategy is adopted for acquisition and recovery. The proposed compressed sensing strategy focuses the measurements on the most perceptually pronounced coefficients. Three weighting schemes are developed and compared with standard CS. Simulation results demonstrate that the proposed framework provides a significant improvement in its three different setups over standard CS in terms of both standard and perceptual objective quality assessment metrics.