Color ghost imaging through the scattering media based on A-cGAN.

Area of Science:

• Optical Imaging
• Computational Imaging
• Deep Learning

Background:

• Ghost imaging is crucial for optical imaging.
• Imaging through scattering media presents significant challenges.
• Achieving high-fidelity color reconstruction in such conditions is difficult.

Purpose of the Study:

• To develop a deep learning method for color ghost imaging through scattering media.
• To enhance the generation ability for reconstructing detailed color images.
• To achieve results that align with human perception and target images.

Main Methods:

• Proposed a novel deep learning approach for color ghost imaging.
• Utilized high generation ability within the deep learning model.
• Tested the method's performance across various scattering intensities.

Main Results:

• Successfully reconstructed detailed color images through scattering media.
• The reconstructed images closely matched target color pictures and human perception.
• Effective imaging was achieved even at a low sampling rate of 0.1.
• The method demonstrated robustness against different scattering intensities.

Conclusions:

• The proposed deep learning method enables effective color ghost imaging through scattering media.
• The technique provides high-quality image reconstruction with rich details.
• This approach offers a promising solution for imaging in challenging scattering environments.