Aperture Diffraction for Compact Snapshot Spectral Imaging

TL;DR

This paper introduces a compact snapshot spectral imaging system called ADIS, combining diffraction-based optical design with a novel transformer-based reconstruction algorithm to achieve high-resolution spectral imaging in a small form factor.

Contribution

The paper presents a new optical design and a deep learning-based reconstruction method for compact, high-resolution spectral imaging without increasing system size.

Findings

Achieved sub-super-pixel spatial resolution

Demonstrated high spectral resolution imaging

System requires no additional physical footprint

Abstract

We demonstrate a compact, cost-effective snapshot spectral imaging system named Aperture Diffraction Imaging Spectrometer (ADIS), which consists only of an imaging lens with an ultra-thin orthogonal aperture mask and a mosaic filter sensor, requiring no additional physical footprint compared to common RGB cameras. Then we introduce a new optical design that each point in the object space is multiplexed to discrete encoding locations on the mosaic filter sensor by diffraction-based spatial-spectral projection engineering generated from the orthogonal mask. The orthogonal projection is uniformly accepted to obtain a weakly calibration-dependent data form to enhance modulation robustness. Meanwhile, the Cascade Shift-Shuffle Spectral Transformer (CSST) with strong perception of the diffraction degeneration is designed to solve a sparsity-constrained inverse problem, realizing the volume reconstruction from 2D measurements with Large amount of aliasing. Our system is evaluated by elaborating the imaging optical theory and reconstruction algorithm with demonstrating the experimental imaging under a single exposure. Ultimately, we achieve the sub-super-pixel spatial resolution and high spectral resolution imaging. The code will be available at: https://github.com/Krito-ex/CSST.