Computational underwater ghost imaging based on scattering-and-absorption degradation.

Area of Science:

• Optics
• Computational Imaging
• Oceanography

Background:

• Underwater imaging is degraded by scattering and absorption.
• Computational ghost imaging (CGI) is sensitive to these underwater environmental factors.

Purpose of the Study:

• To propose a novel anti-degradation underwater computational ghost imaging (AUGI) method.
• To enhance image reconstruction quality in degraded underwater environments.

Main Methods:

• Developed a physical degradation model for underwater forward degradation.
• Implemented the anti-degradation underwater computational ghost imaging (AUGI) method.
• Validated performance using simulations and experimental tests in an artificial submarine environment.

Main Results:

• AUGI improved reconstructed image quality by approximately 10% compared to differential ghost imaging (DGI).
• Performance gains were measured using peak signal-to-noise ratio (PSNR) and structural similarity (SSIM).
• Experimental results confirmed the method's effectiveness in simulated underwater conditions.

Conclusions:

• The proposed AUGI method effectively mitigates degradation in underwater computational ghost imaging.
• The method demonstrates superior performance and is expected to have broad applications in underwater imaging.