Enhanced Infrared Vision by Nonlinear Up-Conversion in Nonlocal Metasurfaces

Area of Science:

• Optics and Photonics
• Materials Science
• Image Processing

Background:

• Short-wave infrared (SWIR) imaging is crucial for surveillance, autonomous navigation, and biological applications.
• Existing SWIR technologies face limitations like large size, thermal noise, and inability to combine infrared and visible imaging.

Purpose of the Study:

• To demonstrate a novel method for infrared imaging using nonlinear up-conversion.
• To develop an ultra-compact, high-quality-factor resonant metasurface for efficient SWIR detection and imaging.

Main Methods:

• Utilized a lithium niobate resonant metasurface for nonlinear optical up-conversion.
• Demonstrated infrared imaging by converting SWIR light to the visible spectrum.
• Investigated the performance of the metasurface under nonlocality conditions.

Main Results:

• Achieved high conversion efficiency and resolution in SWIR imaging.
• Successfully obtained clear infrared images using the compact metasurface.
• Showcased the potential for edge-detection image processing integrated with up-conversion imaging.

Conclusions:

• The developed lithium niobate metasurface offers a compact and efficient solution for SWIR imaging.
• This technology enables augmented imaging capabilities, improving applications like advanced night vision.
• The findings pave the way for next-generation infrared imaging systems with enhanced performance and versatility.