In the video signal acquisition process on the basis of compressed sensing,the quantization method of measured values influences the reconstructed quality remarkably.In order to design a high-performance quantiza- tion method of measured values,a progressive quantization algorithm for compressed video sensing measurements named VPQ (Video Progress Quantization) is proposed on the basis of the inter-frame correlation of videos and the characteristics of measured compressed video sensing signals.In this algorithm,the measured non-key frames are quantized and only some bitplanes with less importance are transmitted.At the decoder,neighbor reconstructed frames are applied to motion estimation to generate the side information of non-key frames,and then the non-key frame measurements are estimated by measuring the side information frame.Finally,in combination with the bit- planes with less importance transmitted from the encoder,accurate measurements are obtained via the inverse quantization of progressive quantization.Experimental results show that,in comparison with uniform scalar quanti- zation,the proposed VPQ algorithm helps greatly decrease the code rate without additional complexity and recon- struction quality degradation; and that it is of higher rate-distortion performance,with a gain ranging from 0. 5 to 2. 0 dB for different sequences.