中文摘要：

为了进一步提高视频压缩感知方案的重构图像质量，提出了一种新的自适应采样方案。在该方案中，根据不同图像块的稀疏度自适应分配采样率。在对各图像块分类判决时，首先判断图像块在离散余弦变换域的稀疏度．其次结合该图像块与其参考帧之间的时域相关性，确定图像块的分类。实验结果表明，与现有的自适应采样率分配方案相比．该算法可获得0．5dB左右的峰值信噪比增益。

英文摘要：

To improve the performance of compressed video sensing（CVS）,a new adaptive sampling rate scheme is proposed in this pape. In such a scheme, the sampling rate is allocated according to the sparsity of each image block. Firstly, the sparsity in discrete cosine transform （DCT） domain for each block is estimated. Then, the classification of image block is determined according to both temporal correlation and spatial sparsity. Experimental results show that compared with the existing adaptive rate CVS methods, this proposed one can get about 0.5 dB Peak Signal to Noise Ratio（PSNR） increment.