Learning Extended Depth of field Hyperspectral Imaging

We propose a learning-based method for snapshot hyper-spectral (HS) imaging of deep 3D scenes. The method combines computational HS imaging and extended depth of field (EDoF) imaging capabilities in a single framework, resulting in novel EDoF-HS camera designs. The camera system incorporates a diffractive optical element at the aperture position, a CFA in front of the sensor and a residual dense network at the post-processing stage. These optical and neural components are jointly optimized through end-to-end learning procedure. We demonstrate high quality HS image reconstructions for scenes as deep as 4 diopters.