Coding Convolutional Neural Networks as Spectral Transmittance for Intelligent Hyperspectral Remote Sensing in a Snapshot

The principle and procedure of coding a convolutional neural network (CNN) in terms of the spectral transmittance of a programmable optical filter are proposed and discussed. They exhibit an intrinsic link between the CNNs and the optical filters, which leads to a methodology by which optical imaging through such spectral transmittance can be seen as equivalent to the results of hyperspectral data numerically postprocessed by the CNN. In such a manner, hyperspectral data acquisition and CNN postprocessing can be implemented simultaneously by the physical process of optical imaging in a snapshot; thus, more intelligent, informative, and real-time optical detection and sensing in the remote sensing applications can be achieved.