Tunable-liquid-crystal-filter-based low-light-level color night vision system and its image processing method

Area of Science:

• Optoelectronics and Imaging Systems
• Computer Vision and Image Processing

Background:

• Traditional night vision systems often struggle to provide clear color images at low light levels.
• Existing low-light-level (LLL) imaging technologies face challenges in color fidelity and noise reduction.

Purpose of the Study:

• To introduce and validate a novel single-channel time-division filtering low-light-level color night vision system (3LCNV).
• To enhance color visibility and reduce noise in LLL night vision imagery.

Main Methods:

• Developed a 3LCNV system integrating a tunable liquid crystal filter, GaAsP image intensifier, and CMOS camera.
• Implemented an image enhancement and color reconstruction algorithm including overexposure-against white balance, color correction matrix (CCM) correction, and color image denoising.
• Verified the system's performance in achieving LLL color imaging with high sensitivity.

Main Results:

• The 3LCNV system successfully achieved natural and clear color imaging at illuminance levels as low as 10^-4 lx.
• The image enhancement algorithm significantly improved color visibility while reducing color differences and image noise.
• The system demonstrated enhanced sensitivity for LLL imaging applications.

Conclusions:

• The proposed 3LCNV system effectively overcomes the limitations of traditional night vision, providing high-quality color images in extremely low light.
• This technology offers a significant advancement for improving night-time observations across various applications.
• The developed image processing algorithm is crucial for achieving accurate color reconstruction and noise suppression in LLL conditions.