Real-Time Enhancement of Low-Quality Video for Constrained Camera Systems

Deploying high-spec cameras in video systems often falls short of user expectations. Leveraging advancements in deep learning, we propose a mobile, lightweight, real-time video enhancement system. Our approach adopts cutting-edge models and introduces novel optimization techniques for real-time streaming, improving low-resolution, grayscale, and low frame-rate videos. Preliminary evaluations show significant improvements in PSNR and SSIM, while visual assessments confirm substantial quality enhancements while maintaining real-time processing requirements.