Abstract

This paper presents the fifirst snapshot hyperspectral light fifield imager in practice. Specififically, we design a novel hybrid camera system to obtain two complementary measurements that sample the angular and spectral dimensions respectively. To recover the full 5D hyperspectral light fifield from severely undersampled measurements, we then propose an effificient computational reconstruction algorithm by exploiting the large correlations across the angular and spectral dimensions through self-learned dictionaries. Simulation on an elaborate hyperspectral light fifield dataset validates the effectiveness of the proposed approach. Hardware experimental results demonstrate that, for the fifirst time to our knowledge, a 5D hyperspectral light fifield containing 9 × 9 angular views and 27 spectral bands can be acquired in a single shot