ReconNet: Non-Iterative Reconstruction of Images from Compressively Sensed Random Measurements

CVPR 2016 Kuldeep KulkarniSuhas LohitPavan TuragaRonan KervicheAmit Ashok

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 as input and outputs an intermediate reconstruction... (read more)

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