An Acquisition Method for Visible and Near Infrared Images from Single CMYG Color Filter Array-Based Sensor

Area of Science:

• Computer Vision
• Image Processing
• Optical Engineering

Background:

• Near-infrared (NIR) imaging is crucial for applications like banknote recognition, vein detection, and surveillance.
• Simultaneous capture of NIR and visible light images is often required.
• Existing systems with separate sensors for NIR and visible light are bulky and expensive.

Purpose of the Study:

• To develop a cost-effective, single-sensor imaging system for simultaneous visible and NIR image acquisition.
• To propose a novel signal separation method for mixed spectral data.
• To enhance the quality of separated images through denoising.

Main Methods:

• A single-sensor imaging system utilizing a cyan, magenta, yellow, and green color filter array.
• Development of a separation matrix derived from mathematical modeling and experimental data.
• Application of a denoising process to improve separated image quality.

Main Results:

• Successful separation of mixed visible and NIR signals into individual RGB and NIR images.
• Achieved average peak-signal-to-noise-ratio (PSNR) of 37.04 dB for RGB and 33.29 dB for NIR images.
• Demonstrated superior performance over related work, with PSNR improvements of 6.72 dB (RGB) and 2.55 dB (NIR).

Conclusions:

• The proposed single-sensor method effectively separates visible and NIR light signals.
• This approach offers a practical and cost-efficient alternative to multi-sensor systems.
• The method significantly enhances image quality and separation performance.