A New Block Compressive Sensing to Control the Number of Measurements
Compressive Sensing (CS) aims to recover a sparse signal from a small number of projections onto random vectors. Be- cause of its great practical possibility, both academia and in- dustries have made efforts to develop the CS’s reconstruction performance, but most of existing works remain at the theo- retical study. In this paper, we propose a new Block Compres- sive Sensing (nBCS), which has several benefits compared to the general CS methods. In particular, the nBCS can be dynamically adaptive to varying channel capacity because it conveys the good inheritance of the wavelet transform.