Quantization effects on Compressed Sensing Video

Compressed Video Sensing (CVS) is the application of the theory and principles of Compressed Sensing to video coding. Previous research has largely ignored the effects of quantization on the random measurements. In this paper, we showed that Gaussian quantization of the CVS coefficients produce higher quality reconstructed videos compared to using MPEG and uniform quantization. Furthermore, the quantization matrix is robust against variations in the mean and standard deviations of the CS measurements among frames. Our work shows how quantization can be implemented for a practical CVS codec.