Multi-exposure color imaging with stacked thin-film luminescent concentrators

We present a fully transparent, scalable, and flexible color image sensor that consists of stacked thin-film luminescent concentrators (LCs). At each layer, it measures a Radon transform of the corresponding LC's spectral responses. Color images are then reconstructed through inverse Radon transforms that are obtained using machine learning. A high sampling rate in Radon space allows encoding multiple exposures to cope with under- and overexposed cases in one recording. Thus, our sensor simultaneously measures multiple spectral responses in different LC layers and multiple exposures in different Radon coefficients per layer. We also show that machine learning enables adequate three-channel image reconstruction from the response of only two LC layers.