Compressive sensing of images based on discrete periodic Radon transform

摘要

A new compressive sensing (CS) scheme using the structured random matrix and the discrete periodic Radon transform (DPRT) is proposed. The new scheme first pre-randomises the sensing image and the DPRT is applied to the randomised samples to generate the so-called DPRT projections. They are then randomly selected to obtain the final sensing measurements. As the DPRT is friendly to hardware/optics implementation, it improves the operability and lowers the cost for real-time CS applications. Compared with other similar transforms such as the Walsh-Hadamard transform, the proposed DPRT scheme gives much better reconstructed images as shown in the simulation results.