Compressive video sampling

Compressive sampling is a novel framework that exploits sparsity of a signal in a transform domain to perform sampling below the Nyquist rate. In this paper, we apply compressive sampling to significantly reduce the sampling rate of video. A practical system is developed that first splits each video frame into non-overlapping blocks of equal size. Compressive sampling is then performed on sparse blocks, determined by predicting sparsity based on previous reference frames which are sampled conventionally. The blocks identified as sparse are reconstructed using the orthogonal matching pursuit algorithm, whereas the remaining blocks are sampled fully. Thus, the acquisition complexity and sampling time are reduced, while exploiting the local sparsity, within the DCT domain, of a video stream. Our simulation results indicate up to 50% saving in acquisition for Y-components of video with very small performance loss compared to traditional sampling.