Physics / mechanism
Hyperspectral sensing captures spatially-resolved spectral data across tens to hundreds of contiguous narrow bands (typically 5–20 nm FWHM) spanning UV through LWIR, versus RGB’s three broad channels. Detectors — InGaAs (SWIR, 900–1700 nm), HgCdTe (MWIR/LWIR), or Si CMOS (VIS-NIR) — are paired with dispersive elements (prism-grating, Fabry-Perot MEMS, or acousto-optic tunable filters) or computed tomography approaches (snapshot mosaic sensors). Key parameters: spectral resolution, spatial resolution, SNR, and frame rate trade off against each other hard. State of the art: snapshot mosaic sensors now hit >100 fps at sub-10 nm resolution; MEMS Fabry-Perot arrays are shrinking the form factor toward chip-scale.
Competitive landscape
Multispectral (4–20 fixed bands) is cheaper, faster, and adequate for many classification tasks — the main competitive pressure. Raman spectroscopy offers higher chemical specificity but requires contact or near-contact geometry. Fluorescence LiDAR adds depth. Mid-IR laser absorption (TDLAS, QCL-based) beats hyperspectral on selectivity for gas-phase analytes. Thermal IR cameras cover temperature mapping without spectral resolution. The real competitive question is whether the application needs continuous spectral curves or just band ratios.
| Technique | Spectral resolution | Standoff / field-use | Cost vector |
|---|---|---|---|
| Hyperspectral | 5–20 nm, contiguous | Yes | Falling fast |
| Multispectral | Fixed bands, ~10–20 | Yes | Low |
| Raman | Sub-nm | Limited | High |
Companies using
Connected ideas
Sources
Frontier (open questions)
- To be added.