Computational Spectral Imaging with Unified Encoding Model: A
  Comparative Study and Beyond
Xinyuan Liu Lizhi Wang Lingen Li Chang Chen Xue Hu Fenglong Song Youliang Yan
Computational spectral imaging is drawing increasing attention owing to the
snapshot advantage, and amplitude, phase, and wavelength encoding systems are
three types of representative implementations. Fairly comparing and
understanding the performance of these systems is essential, but challenging
due to the heterogeneity in encoding design. To overcome this limitation, we
propose the unified encoding model (UEM) that covers all physical systems using
the three encoding types. Specifically, the UEM comprises physical amplitude,
physical phase, and physical wavelength encoding models that can be combined
with a digital decoding model in a joint encoder-decoder optimization framework
to compare the three systems under a unified experimental setup fairly.
Furthermore, we extend the UEMs to ideal versions, namely, ideal amplitude,
ideal phase, and ideal wavelength encoding models, which are free from physical
constraints, to explore the full potential of the three types of computational
spectral imaging systems. Finally, we conduct a holistic comparison of the
three types of computational spectral imaging systems and provide valuable
insights for designing and exploiting these systems in the future.