Computational Spectral Imaging with Unified Encoding Model: A Comparative Study and Beyond

TL;DR

This paper introduces a unified encoding model for computational spectral imaging, enabling fair comparison of amplitude, phase, and wavelength encoding systems, and explores their full potential through idealized models.

Contribution

The paper proposes the unified encoding model (UEM) that encompasses all three encoding types and extends it to ideal models for comprehensive system comparison.

Findings

Holistic comparison of three spectral imaging systems

Insights into the design and optimization of encoding systems

Demonstration of the full potential of each encoding type

Abstract

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.