Snapshot hyperspectral imaging avoids sequential scanning, but systems
that jointly achieve stable reconstruction, low cost, and compact optics
remain limited. We present a snapshot hyperspectral imaging system based
on angular-to-spectral diversity conversion. A tapered kaleidoscope
creates replicated views with distinct incidence directions, and a
directly attached birefringent filter converts them into
view-channel-dependent spectral transmittances, yielding complementary
measurements that better condition the inverse problem for more stable
single-shot spectral reconstruction. The system preserves a simple
pixel-wise linear model for fast non-learning-based reconstruction and
uses only off-the-shelf components without relay optics or cascaded
modules. We select the birefringent filter configuration using a
condition-number-based criterion and validate the system on both
synthetic and real data.
21 cm
compact add-on
25 bands
spectral reconstruction
430–670 nm
spectral range
No learning
pixel-wise inverse solver
System Overview
Our system converts angular diversity into spectral-response diversity
in a compact optical add-on. A tapered kaleidoscope generates multiple
replicated views, and a birefringent filter modulates each view
differently depending on incidence direction. These complementary
measurements are then used to reconstruct the hyperspectral cube.
01
Replicate views
The tapered kaleidoscope produces multiple views of the same scene
with different incidence directions.
02
Convert angle to spectrum
The birefringent filter changes its spectral transmittance with
incidence direction, creating complementary spectral measurements.
03
Reconstruct the cube
Registered measurements are combined through a simple pixel-wise
linear model to recover 25-band hyperspectral data.
Results
ColorChecker Validation
Real-data reflectance reconstruction over 25 bands from
430 nm to 670 nm. The reconstruction achieves 27.4 dB PSNR
over all 24 patches and wavelengths.
Real-Scene Reconstruction
A leaf, flower, and printed materials are reconstructed using
the same prototype and reconstruction pipeline, showing
material-dependent spectral variation in a non-flat scene.
BibTeX
@InProceedings{Kazuma2026A2SHSI,
author="Fujiwara, Kazuma
and Funatomi, Takuya
and Kitano, Kazuya
and Fujimura, Yuki
and Mukaigawa, Yasuhiro",
editor="Favaro, Paolo
and Kukelova, Zuzana
and Maki, Atsuto
and Rohrbach, Anna
and Schindler, Konrad
and Tombari, Federico",
title="Compact Low-Cost Hyperspectral Imaging via Angular-to-Spectral Diversity Conversion",
booktitle="Computer Vision -- ECCV 2026",
year="2026",
publisher="Springer Nature Switzerland",
address="Cham",
pages="589--606",
isbn="978-3-032-37196-6"
}