Wednesday, June 05, 2024

Night-vision lenses so thin and light that we can all see in the dark

Good news for night owls!

"... Researchers from the ARC Centre of Excellence for Transformative Meta-Optical Systems (TMOS) in Australia have been on a quest to make night vision accessible and wearable, doing away with bulky and expensive headsets and lens attachments. ...
This new tech also captures the visible and non-visible (or infrared) light in one image as you look through the 'lens.' Traditionally, night-vision systems capture side-by-side views from each spectrum, so they can't produce identical images. ...
“This is the first demonstration of high resolution up-conversion imaging from 1550-nm infrared to visible 550-nm light in a non-local metasurface," ... "We choose these wavelengths because 1,550 nm, an infrared light, is commonly used for telecommunications, and 550 nm is visible light to which human eyes are highly sensitive. Future research will include expanding the range of wavelengths the device is sensitive to, aiming to obtain broadband IR imaging, as well as exploring image processing, including edge detection.” ..."

From the abstract:
"The ability to detect and image short-wave infrared light has important applications in surveillance, autonomous navigation, and biological imaging. However, the current infrared imaging technologies often pose challenges due to large footprint, large thermal noise and inability to augment infrared and visible imaging. Here, infrared imaging is demonstrated by nonlinear up-conversion to the visible in an ultra-compact, high-quality-factor lithium niobate resonant metasurface. Images with high conversion efficiency and resolution quality are obtained despite the strong nonlocality of the metasurface. The possibility of edge-detection image processing augmented with direct up-conversion imaging for advanced night vision applications is further shown."

Night-vision lenses so thin and light that we can all see in the dark



Figure 1 Infrared (IR) to visible (VIS) up-conversion for vision applications.


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