The model parameters of Video Compressed Sensing of Linear Dynamic System (CS-LDS) can be estimated directly from random sampling data. If all video frames are sampled in the same way, the sampling data will be redundant. To solve this problem, an adaptive improvement algorithm based on adaptive compression sampling technology was proposed in this paper. Firstly, a Linear Dynamic System (LDS) model of the video signal was established. And then the sampling data of video signal was obtained by using the adaptive compression sampling method. Finally, the model parameters were estimated and the video signal was reconstructed by the sampling data. Without affecting the video reconstruction quality, the experimental results show that the proposed algorithm is better than the CS-LDS algorithm, it can not only reduce 20%-40% sampling data in the uniform measurement process, but also save the average running time of 0.1-0.3 s per frame. The improved algorithm reduces the number of samples and the algorithm's running time.