Snapshot Spatiotemporal-Spectral Imaging Enabled by Joint Photonic Encoding

Hyperspectral imaging (HSI) enables simultaneous acquisition of spectral and spatial information and has been widely adopted across science and engineering. However, existing HSI systems are primarily designed for x-y-λ datacube acquisition, with the temporal dimension insufficiently incorporated and limiting their ability to capture rapid variations in spatial structures or spectral signatures. Here we report Spectra4D (x, y, λ, t), a snapshot spatiotemporal-spectral imaging architecture that enables high-dimensional and high-resolution observation of dynamic scenes beyond the native camera frame-rate limit. Enabled by joint photonic encoding approach, Spectra4D synergizes high-speed temporal modulation with on-sensor spectral multiplexing to jointly encode spatiotemporal and spectral information into a single compressed exposure, which is computationally reconstructed using a dual-mask guided reconstruction network. Experiments demonstrate that Spectra4D reconstructs 28 visible spectral channels under 4× temporal compression, achieving spectral fidelity above 96.5% and pixel-level localization accuracy across continuous multi-frame sequences. We further validate the capability of Spectra4D in dynamic spatio-spectral scenarios, including dual-color fluorescent microsphere tracking and frame-resolved elemental monitoring in flame combustion. In summary, Spectra4D presents a practical and scalable route toward temporally resolved spatio-spectral imaging of dynamic processes with rapidly varying spectral features.