FourierNetsenablethedesignofhighlynon-local opticalencodersforcomputationalimaging

More challenging computational imaging applications, such as3D snapshot microscopywhichcompresses 3Dvolumes intosingle2Dimages, require ahighly non-local optical encoder. We show that existing deep network decoders have a locality bias which prevents the optimization of such highly non-local optical encoders. We address this with a decoder based on a shallow neural network architecture using global kernel Fourier convolutional neural networks (FourierNets).