2016
ReconNet: Non-Iterative Reconstruction of Images From Compressively Sensed Measurements
CVPR 2016poster
The goal of this paper is to present a non-iterative and more importantly an extremely fast algorithm to reconstruct images from compressively sensed (CS) random measurements. To this end, we propose a novel convolutional neural network (CNN) architecture which takes in CS measurements of an image…