Coherence- and scattering-universal diffractive neural network for imaging through scattering media

We propose a design method for a diffractive neural network (DNN) for imaging through scattering media, offering robustness against the spatial coherence of illumination, scattering strength, and scattering dynamics. The DNN, composed of layers of diffractive optical elements (DOEs), optically reproduces the intensity distributions of objects behind scattering media without any computational processing. Datasets with various degrees of spatial coherence, scattering strength, and scattering dynamics are provided during the training process to achieve this robustness. We demonstrate the proposed method through numerical calculations and show its promising capability for DOE design. This method unifies and generalizes techniques for imaging through scattering media, which are currently fragmented by specific scenarios, pushing them to a new frontier.