On-chip Real-time Hyperspectral Imager with Full CMOS Resolution Enabled by Massively Parallel Neural Network
arxiv(2024)
摘要
Traditional spectral imaging methods are constrained by the time-consuming
scanning process, limiting the application in dynamic scenarios. One-shot
spectral imaging based on reconstruction has been a hot research topic recently
and the primary challenges still lie in both efficient fabrication techniques
suitable for mass production and the high-speed, high-accuracy reconstruction
algorithm for real-time spectral imaging. In this study, we introduce an
innovative on-chip real-time hyperspectral imager that leverages nanophotonic
film spectral encoders and a Massively Parallel Network (MP-Net), featuring a 4
* 4 array of compact, all-dielectric film units for the micro-spectrometers.
Each curved nanophotonic film unit uniquely modulates incident light across the
underlying 3 * 3 CMOS image sensor (CIS) pixels, enabling a high spatial
resolution equivalent to the full CMOS resolution. The implementation of
MP-Net, specially designed to address variability in transmittance and
manufacturing errors such as misalignment and non-uniformities in thin film
deposition, can greatly increase the structural tolerance of the device and
reduce the preparation requirement, further simplifying the manufacturing
process. Tested in varied environments on both static and moving objects, the
real-time hyperspectral imager demonstrates the robustness and high-fidelity
spatial-spectral data capabilities across diverse scenarios. This on-chip
hyperspectral imager represents a significant advancement in real-time,
high-resolution spectral imaging, offering a versatile solution for
applications ranging from environmental monitoring, remote sensing to consumer
electronics.
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