Cascaded reconstruction network for compressive image sensing

The theory of compressed sensing (CS) has been successfully applied to image compression in the past few years, whose traditional iterative reconstruction algorithm is time-consuming. Fortunately, it has been reported deep learning-based CS reconstruction algorithms could greatly reduce the computational complexity. In this paper, we propose two efficient structures of cascaded reconstruction networks corresponding to two different sampling...