Compressed video sensing using adaptive sampling rate

Abstract

Compressive video sampling is an application of compressed sensing (CS) theory which samples a signal below the Shannon-Nyquist rate. In this paper, we present a compressed video sensing method that samples the blocks with adaptive sampling rate. The edge of the image is exploited to define a deficiency factor for blocks. Considering this factor, we determine sampling rates independently for each block. The simulation results show that the proposed method outperforms the conventional CS in image quality for the same compression ratio.