High quality computational ghost imaging using multi-fluorescent screen.

Area of Science:

• Optics
• Computational Imaging
• Fluorescence Spectroscopy

Background:

• Computational ghost imaging (GI) is a technique that reconstructs images using non-correlated light patterns.
• Traditional GI methods often face limitations in image quality, such as low visibility and signal-to-noise ratio (SNR).
• Monochrome fluorescent screens have shown limited effectiveness in improving GI performance.

Purpose of the Study:

• To propose and evaluate an alternative scheme for enhancing computational ghost imaging features.
• To investigate the impact of using a multi-fluorescent screen on ghost image quality.
• To demonstrate the potential for reduced measurement requirements in GI.

Main Methods:

• A novel computational ghost imaging scheme utilizing a three-color fluorescent screen was developed.
• Simulations were conducted to assess image quality metrics including visibility, SNR, and contrast-to-noise ratio (CNR).
• Experimental validation was performed to confirm simulation results.

Main Results:

• The use of a multi-fluorescent screen significantly improved ghost image quality compared to monochrome screens or ordinary GI.
• Visibility, SNR, and CNR showed improvements of 65%, 36%, and 95% respectively over 2000 shots.
• Successful reconstruction of ghost images was achieved with as few as 25 shots by increasing screen colors, a feat not possible with ordinary GI.

Conclusions:

• A multi-fluorescent screen offers a highly effective method for enhancing computational ghost imaging.
• This approach leads to substantial improvements in key image quality parameters.
• The proposed technique enables high-quality GI reconstruction with a significantly reduced number of measurements.