The ever-increasing adoption of machine vision is creating extensive opportunities for new and improved image sensors. For example, short-wave infra-red (SWIR, 1000-2000 nm) sensing offers multiple benefits to supplement conventional visible-range CMOS sensors, including reduced optical scattering (useful for seeing through fog and hence for autonomous vehicles), mapping thermal profiles, and distinguishing visually similar materials. At present, SWIR imaging is dominated by expensive InGaAs sensors, creating a clear opportunity for a disruptive, low-cost alternative.
In addition to imaging over a broader spectral range, further innovations include imaging over a larger area, acquiring spectral data at each pixel, and simultaneously increasing temporal resolution and dynamic range. These promising innovations include event-based vision and hyperspectral imaging.
- The motivation and applications for emerging image sensors, which span autonomous vehicles, drones, industrial quality control, and more
- The current technological and commercial status of the emerging SWIR imaging technologies competing to replace InGaAs
- Discussion of event-based vision and hyperspectral imaging
- Identification of market challenges